- Tips & Tricks of Deploying Deep Learning Webapp on Heroku Cloud - Dec 24, 2021.
Learn model deployment issues and solutions on deploying a TensorFlow-based image classifier Streamlit app on a Heroku server.
Applications, Docker, DVC, GitHub, Heroku, Streamlit, TensorFlow
- On-Device Deep Learning: PyTorch Mobile and TensorFlow Lite - Nov 22, 2021.
PyTorch and TensorFlow are the two leading AI/ML Frameworks. In this article, we take a look at their on-device counterparts PyTorch Mobile and TensorFlow Lite and examine them more deeply from the perspective of someone who wishes to develop and deploy models for use on mobile platforms.
Deep Learning, Mobile, PyTorch, TensorFlow
The 20 Python Packages You Need For Machine Learning and Data Science - Oct 14, 2021.
Do you do Python? Do you do data science and machine learning? Then, you need to do these crucial Python libraries that enable nearly all you will want to do.
Data Science, Keras, Machine Learning, Matplotlib, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn, TensorFlow
- A Breakdown of Deep Learning Frameworks - Sep 23, 2021.
Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.
Deep Learning, Keras, MATLAB, MXNet, PyTorch, TensorFlow
- Introducing TensorFlow Similarity - Sep 17, 2021.
TensorFlow Similarity is a newly-released library from Google that facilitates the training, indexing and querying of similarity models. Check out more here.
Google, Neural Networks, TensorFlow
- High-Performance Deep Learning: How to train smaller, faster, and better models – Part 5 - Jul 16, 2021.
Training efficient deep learning models with any software tool is nothing without an infrastructure of robust and performant compute power. Here, current software and hardware ecosystems are reviewed that you might consider in your development when the highest performance possible is needed.
Deep Learning, Efficiency, Google, Hardware, Machine Learning, NVIDIA, PyTorch, Scalability, TensorFlow
- Beginners Guide to Debugging TensorFlow Models - Jun 15, 2021.
If you are new to working with a deep learning framework, such as TensorFlow, there are a variety of typical errors beginners face when building and training models. Here, we explore and solve some of the most common errors to help you develop a better intuition for debugging in TensorFlow.
Beginners, Deep Learning, TensorFlow
- What makes a winning entry in a Machine Learning competition? - May 5, 2021.
So you want to show your grit in a Kaggle-style competition? Many, many others have the same idea, including domain experts and non-experts, and academic and corporate teams. What does it take for your bright ideas and skills to come out on top of thousands of competitors?
Challenge, Competition, Kaggle, Machine Learning, PyTorch, TensorFlow
The Most In-Demand Skills for Data Scientists in 2021 - Apr 15, 2021.
If you are preparing to make a career as a Data Scientist or are looking for opportunities to skill-up in your current role, this analysis of in-demand skills for 2021, based on over 15,000 Data Scientist job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
AWS, Data Science Skills, Python, PyTorch, R, scikit-learn, SQL, TensorFlow
Top 10 Python Libraries Data Scientists should know in 2021 - Mar 24, 2021.
So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.
Data Science, Keras, numpy, Pandas, Python, scikit-learn, Seaborn, TensorFlow
- 6 Data Science Certificates To Level Up Your Career - Feb 18, 2021.
Anyone looking to obtain a data science certificate to prove their ability in the field will find a range of options exist. We review several valuable certificates to consider that will definitely pump up your resume and portfolio to get you closer to your dream job.
Career Advice, Certificate, Cloudera, Data Science Certificate, Google, IBM, Microsoft Azure, SAS, TensorFlow
- Hugging Face Transformers Package – What Is It and How To Use It - Feb 16, 2021.
The rapid development of Transformers have brought a new wave of powerful tools to natural language processing. These models are large and very expensive to train, so pre-trained versions are shared and leveraged by researchers and practitioners. Hugging Face offers a wide variety of pre-trained transformers as open-source libraries, and you can incorporate these with only one line of code.
Deep Learning, Hugging Face, Natural Language Generation, NLP, PyTorch, TensorFlow, Transformer, Zero-shot Learning
- Who is fit to lead data science? - Feb 9, 2021.
Data science success depends on leaders, not the latest hands-on programming skills. So, we need to start looking for the right leadership skills and stop stuffing job postings with requirements for experience in the most current development tools.
Business, Career Advice, Data Leadership, Data Science, Data Scientist, TensorFlow
- Saving and loading models in TensorFlow — why it is important and how to do it - Feb 3, 2021.
So much time and effort can go into training your machine learning models. But, shut down the notebook or system, and all those trained weights and more vanish with the memory flush. Saving your models to maximize reusability is key for efficient productivity.
Deep Learning, Machine Learning, TensorFlow
- Mastering TensorFlow Variables in 5 Easy Steps - Jan 20, 2021.
Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.
Neural Networks, Python, TensorFlow
- Pruning Machine Learning Models in TensorFlow - Dec 4, 2020.
Read this overview to learn how to make your models smaller via pruning.
Machine Learning, Modeling, Python, TensorFlow
- Deploying Trained Models to Production with TensorFlow Serving - Nov 30, 2020.
TensorFlow provides a way to move a trained model to a production environment for deployment with minimal effort. In this article, we’ll use a pre-trained model, save it, and serve it using TensorFlow Serving.
Deployment, Modeling, Neural Networks, Python, TensorFlow
- tensorflow + dalex = :) , or how to explain a TensorFlow model - Nov 13, 2020.
Having a machine learning model that generates interesting predictions is one thing. Understanding why it makes these predictions is another. For a tensorflow predictive model, it can be straightforward and convenient develop an explainable AI by leveraging the dalex Python package.
Dalex, Explainability, Explainable AI, Machine Learning, Python, TensorFlow
How to Acquire the Most Wanted Data Science Skills - Nov 13, 2020.
We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.
Algorithms, Amazon, Apache Spark, AWS, Computer Vision, Data Science, Data Science Skills, Deep Learning, Docker, NLP, NoSQL, PyTorch, Reinforcement Learning, TensorFlow
- Mastering TensorFlow Tensors in 5 Easy Steps - Nov 11, 2020.
Discover how the building blocks of TensorFlow works at the lower level and learn how to make the most of Tensor objects.
Deep Learning, Python, Tensor, TensorFlow
PerceptiLabs – A GUI and Visual API for TensorFlow - Oct 27, 2020.
Recently released PerceptiLabs 0.11, is quickly becoming the GUI and visual API for TensorFlow. PerceptiLabs is built around a sophisticated visual ML modeling editor in which you drag and drop components and connect them together to form your model, automatically creating the underlying TensorFlow code. Try it now.
API, Deep Learning, PerceptiLabs, TensorFlow
4 ways to improve your TensorFlow model – key regularization techniques you need to know - Aug 27, 2020.
Regularization techniques are crucial for preventing your models from overfitting and enables them perform better on your validation and test sets. This guide provides a thorough overview with code of four key approaches you can use for regularization in TensorFlow.
Machine Learning, Overfitting, Regularization, TensorFlow
- Must-read NLP and Deep Learning articles for Data Scientists - Aug 21, 2020.
NLP and deep learning continue to advance, nearly on a daily basis. Check out these recent must-read guides, feature articles, and other resources to keep you on top of the latest advancements and ahead of the curve.
Deep Learning, Google, GPT-3, NLP, OpenAI, Privacy, Research, Self-Driving, TensorFlow, Trends
Top Google AI, Machine Learning Tools for Everyone - Aug 18, 2020.
Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.
AI, AutoML, Bias, Data Science Platforms, Datasets, Google, Google Cloud, Google Colab, Machine Learning, TensorFlow
- Building a REST API with Tensorflow Serving (Part 2) - Jul 21, 2020.
This post is the second part of the tutorial of Tensorflow Serving in order to productionize Tensorflow objects and build a REST API to make calls to them.
API, Docker, Keras, Python, TensorFlow
- Recurrent Neural Networks (RNN): Deep Learning for Sequential Data - Jul 20, 2020.
Recurrent Neural Networks can be used for a number of ways such as detecting the next word/letter, forecasting financial asset prices in a temporal space, action modeling in sports, music composition, image generation, and more.
Deep Learning, Python, Recurrent Neural Networks, Sequences, TensorFlow
- Building a REST API with Tensorflow Serving (Part 1) - Jul 15, 2020.
Part one of a tutorial to teach you how to build a REST API around functions or saved models created in Tensorflow. With Tensorflow Serving and Docker, defining endpoint URLs and sending HTTP requests is simple.
API, Keras, Python, TensorFlow
- Generating cooking recipes using TensorFlow and LSTM Recurrent Neural Network: A step-by-step guide - Jul 3, 2020.
A character-level LSTM (Long short-term memory) RNN (Recurrent Neural Network) is trained on ~100k recipes dataset using TensorFlow. The model suggested the recipes "Cream Soda with Onions", "Puff Pastry Strawberry Soup", "Zucchini flavor Tea", and "Salmon Mousse of Beef and Stilton Salad with Jalapenos". Yum!? Follow along this detailed guide with code to create your own recipe-generating chef.
Cooking, Deep Learning, Humor, LSTM, Natural Language Generation, TensorFlow
Getting Started with TensorFlow 2 - Jul 2, 2020.
Learn about the latest version of TensorFlow with this hands-on walk-through of implementing a classification problem with deep learning, how to plot it, and how to improve its results.
Advice, Beginners, Deep Learning, Python, Regularization, TensorFlow
- 6 Easy Steps to Implement a Computer Vision Application Using Tensorflow.js - Jun 18, 2020.
In this article, we are going to see how we can implement computer vision applications using tensorflow.js models.
Computer Vision, Javascript, TensorFlow
- LinkedIn Open Sources a Small Component to Simplify the TensorFlow-Spark Interoperability - May 25, 2020.
Spark-TFRecord enables the processing of TensorFlow’s TFRecord structures in Apache Spark.
LinkedIn, Open Source, Spark, TensorFlow
- TensorFlow Dev Summit 2020: Top 10 Tricks for TensorFlow and Google Colab Users - Apr 8, 2020.
In this piece, we’ll highlight some of the tips and tricks mentioned during this year’s TF summit. Specifically, these tips will help you in getting the best out of Google’s Colab.
Google, Google Colab, TensorFlow, Tips
- Build an app to generate photorealistic faces using TensorFlow and Streamlit - Apr 7, 2020.
We’ll show you how to quickly build a Streamlit app to synthesize celebrity faces using GANs, Tensorflow, and st.cache.
App, GANs, Generative Adversarial Network, Python, Streamlit, TensorFlow
- Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models - Mar 23, 2020.
TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.
Google, Machine Learning, Quantum Computing, TensorFlow
- Tokenization and Text Data Preparation with TensorFlow & Keras - Mar 6, 2020.
This article will look at tokenizing and further preparing text data for feeding into a neural network using TensorFlow and Keras preprocessing tools.
Data Preprocessing, Keras, NLP, Python, TensorFlow, Text Analytics, Tokenization
- TensorFlow 2.0 Tutorial: Optimizing Training Time Performance - Mar 5, 2020.
Tricks to improve TensorFlow training time with tf.data pipeline optimizations, mixed precision training and multi-GPU strategies.
Neural Networks, Optimization, Python, TensorFlow, Training
- Easy Image Dataset Augmentation with TensorFlow - Feb 13, 2020.
What can we do when we don't have a substantial amount of varied training data? This is a quick intro to using data augmentation in TensorFlow to perform in-memory image transformations during model training to help overcome this data impediment.
Data Preprocessing, Image Processing, Image Recognition, Python, TensorFlow
- Intent Recognition with BERT using Keras and TensorFlow 2 - Feb 10, 2020.
TL;DR Learn how to fine-tune the BERT model for text classification. Train and evaluate it on a small dataset for detecting seven intents. The results might surprise you!
BERT, Keras, NLP, Python, TensorFlow
- Transfer Learning Made Easy: Coding a Powerful Technique - Nov 13, 2019.
While the revolution of deep learning now impacts our daily lives, these networks are expensive. Approaches in transfer learning promise to ease this burden by enabling the re-use of trained models -- and this hands-on tutorial will walk you through a transfer learning technique you can run on your laptop.
Accuracy, Deep Learning, Image Classification, Keras, Machine Learning, TensorFlow, Transfer Learning
The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization - Oct 7, 2019.
As a data scientist, your most important skill is creating meaningful visualizations to disseminate knowledge and impact your organization or client. These seven principals will guide you toward developing charts with clarity, as exemplified with data from a recent KDnuggets poll.
Data Science, Data Science Skills, Data Visualization, Excel, Java, Python, Skills, TensorFlow
Which Data Science Skills are core and which are hot/emerging ones? - Sep 17, 2019.
We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.
Career, Data Science Skills, Data Visualization, Deep Learning, Excel, Machine Learning, Poll, Python, PyTorch, Scala, Skills, Statistics, TensorFlow
- TensorFlow Optimization Showdown: ActiveState vs. Anaconda - Sep 5, 2019.
In this TensorFlow tutorial, you’ll learn the impact of optimizing both operators and entire graphs, how to efficiently organize data in training and testing datasets to minimize data shuffling, and how to identify a well-optimized model using Anaconda and ActivePython.
ActiveState, Anaconda, TensorFlow
TensorFlow vs PyTorch vs Keras for NLP - Sep 3, 2019.
These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.
Deep Learning, Exxact, Keras, NLP, PyTorch, TensorFlow
- TensorFlow 2.0: Dynamic, Readable, and Highly Extended - Aug 27, 2019.
With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.
Deep Learning, Deployment, Exxact, TensorFlow
- Understanding Tensor Processing Units - Jul 30, 2019.
The Tensor Processing Unit (TPU) is Google's custom tool to accelerate machine learning workloads using the TensorFlow framework. Learn more about what TPUs do and how they can work for you.
Google, Sciforce, TensorFlow, TPU
Convolutional Neural Networks: A Python Tutorial Using TensorFlow and Keras - Jul 26, 2019.
Different neural network architectures excel in different tasks. This particular article focuses on crafting convolutional neural networks in Python using TensorFlow and Keras.
Convolutional Neural Networks, Keras, Neural Networks, Python, TensorFlow
Training a Neural Network to Write Like Lovecraft - Jul 11, 2019.
In this post, the author attempts to train a neural network to generate Lovecraft-esque prose, known to be awkward and irregular at best. Did it end in success? If not, any suggestions on how it might have? Read on to find out.
Keras, LSTM, Natural Language Generation, Neural Networks, Python, TensorFlow
Data Science Jobs Report 2019: Python Way Up, TensorFlow Growing Rapidly, R Use Double SAS - Jun 17, 2019.
Data science jobs continue to grow in 2019, and this report shares the change and spread of jobs by software over recent years.
Data Science, indeed, Jobs, Python, R, SAS, TensorFlow
- How to Automate Hyperparameter Optimization - Jun 12, 2019.
A step-by-step guide into performing a hyperparameter optimization task on a deep learning model by employing Bayesian Optimization that uses the Gaussian Process. We used the gp_minimize package provided by the Scikit-Optimize (skopt) library to perform this task.
Bayesian, Deep Learning, Hyperparameter, Machine Learning, Neural Networks, Optimization, Python, TensorFlow
What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem - Jun 10, 2019.
We identify the 6 tools in the modern open-source Data Science ecosystem, examine the Python vs R question, and determine which tools are used the most with Deep Learning and Big Data.
Anaconda, Apache Spark, Big Data Software, Deep Learning, Excel, Keras, Poll, Python, R, RapidMiner, scikit-learn, Software, SQL, Tableau, TensorFlow
- Using the ‘What-If Tool’ to investigate Machine Learning models - Jun 6, 2019.
The machine learning practitioner must be a detective, and this tool from teams at Google enables you to investigate and understand your models.
Advice, Data Science Tools, Data Visualization, Machine Learning, TensorFlow
Python leads the 11 top Data Science, Machine Learning platforms: Trends and Analysis - May 30, 2019.
Python continues to lead the top Data Science platforms, but R and RapidMiner hold their share; Almost 50% have used Deep Learning tools; SQL is steady; Consolidation continues.
Pages: 1 2
Anaconda, Apache Spark, Deep Learning, Excel, Keras, Poll, Python, R, RapidMiner, scikit-learn, Software, SQL, TensorFlow
- How to use continual learning in your ML models, June 19 Webinar - May 29, 2019.
This webinar for professional data scientists will go over how to monitor models when in production, and how to set up automatically adaptive machine learning.
cnvrg.io, Kubernetes, Machine Learning, Production, TensorFlow
- How to Automate Tasks on GitHub With Machine Learning for Fun and Profit - May 3, 2019.
Check this tutorial on how to build a GitHub App that predicts and applies issue labels using Tensorflow and public datasets.
Datasets, GitHub, Python, TensorFlow
- Which Deep Learning Framework is Growing Fastest? - May 1, 2019.
In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed?
Data Science, Data Scientist, Deep Learning, fast.ai, Keras, Python, PyTorch, TensorFlow
Another 10 Free Must-See Courses for Machine Learning and Data Science - Apr 5, 2019.
Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.
AI, Data Science, Deep Learning, Keras, Machine Learning, NLP, Reinforcement Learning, TensorFlow, U. of Washington, UC Berkeley, Unsupervised Learning
- How to Train a Keras Model 20x Faster with a TPU for Free - Mar 19, 2019.
This post shows how to train an LSTM Model using Keras and Google CoLaboratory with TPUs to exponentially reduce training time compared to a GPU on your local machine.
Deep Learning, Google Colab, Keras, Python, TensorFlow, TPU
- Comparing MobileNet Models in TensorFlow - Mar 1, 2019.
MobileNets are a family of mobile-first computer vision models for TensorFlow, designed to effectively maximize accuracy while being mindful of the restricted resources for an on-device or embedded application.
Computer Vision, Mobile, Neural Networks, TensorFlow
- TensorFlow.js: Machine learning for the web and beyond - Feb 28, 2019.
TensorFlow.js brings TensorFlow and Keras to the the JavaScript ecosystem, supporting both Node.js and browser-based applications. Read a summary of the paper which describes the design, API, and implementation of TensorFlow.js.
Javascript, Keras, Neural Networks, TensorFlow
- State of the art in AI and Machine Learning – highlights of papers with code - Feb 20, 2019.
We introduce papers with code, the free and open resource of state-of-the-art Machine Learning papers, code and evaluation tables.
AI, Machine Learning, Multitask Learning, NLP, Papers with code, Recommender Systems, Semantic Segmentation, TensorFlow, Transfer Learning
- Deep Multi-Task Learning – 3 Lessons Learned - Feb 15, 2019.
We share specific points to consider when implementing multi-task learning in a Neural Network (NN) and present TensorFlow solutions to these issues.
Deep Learning, Deep Neural Network, Machine Learning, Neural Networks, Optimization, TensorFlow
Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning - Dec 19, 2018.
Here are the top 15 Python libraries across Data Science, Data Visualization. Deep Learning, and Machine Learning.
Data Science, Deep Learning, Machine Learning, Pandas, Python, PyTorch, TensorFlow
- State of Deep Learning and Major Advances: H2 2018 Review - Dec 13, 2018.
In this post we summarise some of the key developments in deep learning in the second half of 2018, before briefly discussing the road ahead for the deep learning community.
Deep Learning, Generative Adversarial Network, NLP, PyTorch, TensorFlow, Trends
- Variational Autoencoders Explained in Detail - Nov 30, 2018.
We explain how to implement VAE - including simple to understand tensorflow code using MNIST and a cool trick of how you can generate an image of a digit conditioned on the digit.
Autoencoder, Deep Learning, Machine Learning, MNIST, TensorFlow
Top 13 Python Deep Learning Libraries - Nov 2, 2018.
Part 2 of a new series investigating the top Python Libraries across Machine Learning, AI, Deep Learning and Data Science.
Caffe, Deep Learning, GitHub, MXNet, Python, PyTorch, TensorFlow, Theano
- Deep Learning Framework Power Scores 2018 - Sep 24, 2018.
Who’s on top in usage, interest, and popularity?
CNTK, Deep Learning, fast.ai, Java, Keras, MXNet, Python, PyTorch, TensorFlow, Theano
Ultimate Guide to Getting Started with TensorFlow - Sep 6, 2018.
Including video and written tutorials, beginner code examples, useful tricks, helpful communities, books, jobs and more - this is the ultimate guide to getting started with TensorFlow.
Deep Learning, Dropout, Python, TensorFlow
- 9 Things You Should Know About TensorFlow - Aug 22, 2018.
A summary of the key points from the Google Cloud Next in San Francisco, "What’s New with TensorFlow?", including neural networks, TensorFlow Lite, data pipelines and more.
Deep Learning, Google, Keras, Machine Learning, Python, TensorFlow
- Setting up your AI Dev Environment in 5 Minutes - Aug 13, 2018.
Whether you're a novice data science enthusiast setting up TensorFlow for the first time, or a seasoned AI engineer working with terabytes of data, getting your libraries, packages, and frameworks installed is always a struggle. Learn how datmo, an open source python package, helps you get started in minutes.
AI, datmo, Development, Docker, Machine Learning, Python, TensorFlow
- Autoregressive Models in TensorFlow - Aug 6, 2018.
This article investigates autoregressive models in TensorFlow, including autoregressive time series and predictions with the actual observations.
Regression, TensorFlow, Time Series
Analyze a Soccer (Football) Game Using Tensorflow Object Detection and OpenCV - Jul 10, 2018.
For the data scientist within you let's use this opportunity to do some analysis on soccer clips. With the use of deep learning and opencv we can extract interesting insights from video clips
Football, Image Recognition, Object Detection, OpenCV, Python, Soccer, TensorFlow, Video recognition, World Cup
- Inside the Mind of a Neural Network with Interactive Code in Tensorflow - Jun 29, 2018.
Understand the inner workings of neural network models as this post covers three related topics: histogram of weights, visualizing the activation of neurons, and interior / integral gradients.
Pages: 1 2
Convolutional Neural Networks, Image Recognition, Neural Networks, Python, TensorFlow
Top 20 Python Libraries for Data Science in 2018 - Jun 27, 2018.
Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment.
Pages: 1 2
Bokeh, Data Science, Keras, Matplotlib, NLTK, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn, SciPy, Seaborn, TensorFlow, XGBoost
The 6 components of Open-Source Data Science/ Machine Learning Ecosystem; Did Python declare victory over R? - Jun 6, 2018.
We find 6 tools form the modern open source Data Science / Machine Learning ecosystem; examine whether Python declared victory over R; and review which tools are most associated with Deep Learning and Big Data.
Anaconda, Apache Spark, Data Science, Keras, Machine Learning, Open Source, Poll, Python, R, RapidMiner, Scala, scikit-learn, TensorFlow
Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis - May 22, 2018.
Python continues to eat away at R, RapidMiner gains, SQL is steady, Tensorflow advances pulling along Keras, Hadoop drops, Data Science platforms consolidate, and more.
Pages: 1 2
Anaconda, Data Mining Software, Data Science Platform, Hadoop, Keras, Poll, Python, R, RapidMiner, SQL, TensorFlow, Trends
- GANs in TensorFlow from the Command Line: Creating Your First GitHub Project - May 16, 2018.
In this article I will present the steps to create your first GitHub Project. I will use as an example Generative Adversarial Networks.
GANs, Generative Adversarial Network, GitHub, Neural Networks, Python, Rubens Zimbres, TensorFlow
Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API - May 15, 2018.
In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.
Pages: 1 2
API, Convolutional Neural Networks, Dropout, Flask, Neural Networks, Python, RESTful API, TensorFlow
- Top 16 Open Source Deep Learning Libraries and Platforms - Apr 24, 2018.
We bring to you the top 16 open source deep learning libraries and platforms. TensorFlow is out in front as the undisputed number one, with Keras and Caffe completing the top three.
Caffe, GitHub, Keras, Machine Learning, Open Source, TensorFlow
- Are High Level APIs Dumbing Down Machine Learning? - Apr 16, 2018.
Libraries like Keras simplify the construction of neural networks, but are they impeding on practitioners full understanding? Or are they simply useful (and inevitable) abstractions?
API, Deep Learning, Francois Chollet, Keras, Machine Learning, Neural Networks, TensorFlow
Top 20 Deep Learning Papers, 2018 Edition - Apr 3, 2018.
Deep Learning is constantly evolving at a fast pace. New techniques, tools and implementations are changing the field of Machine Learning and bringing excellent results.
Algorithms, Deep Learning, Machine Learning, Neural Networks, TensorFlow, Text Analytics, Trends
A “Weird” Introduction to Deep Learning - Mar 30, 2018.
There are amazing introductions, courses and blog posts on Deep Learning. But this is a different kind of introduction.
Pages: 1 2
Deep Learning, Dropout, Neural Networks, Representation, Tensor, TensorFlow
- Using Tensorflow Object Detection to do Pixel Wise Classification - Mar 29, 2018.
Tensorflow recently added new functionality and now we can extend the API to determine pixel by pixel location of objects of interest. So when would we need this extra granularity?
Classification, Image Recognition, Object Detection, Python, TensorFlow
- Comparing Deep Learning Frameworks: A Rosetta Stone Approach - Mar 26, 2018.
A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.
Caffe, CNTK, Deep Learning, GPU, Keras, Microsoft, MXNet, PyTorch, TensorFlow
- Is Google Tensorflow Object Detection API the Easiest Way to Implement Image Recognition? - Mar 1, 2018.
There are many different ways to do image recognition. Google recently released a new Tensorflow Object Detection API to give computer vision everywhere a boost.
API, Image Recognition, TensorFlow
- Top 20 Python AI and Machine Learning Open Source Projects - Feb 20, 2018.
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
GitHub, Machine Learning, Open Source, Python, scikit-learn, TensorFlow
Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch - Feb 20, 2018.
Now you can develop deep learning applications with Google Colaboratory - on the free Tesla K80 GPU - using Keras, Tensorflow and PyTorch.
Pages: 1 2
Deep Learning, Google, Google Colab, Keras, Python, PyTorch, TensorFlow
3 Essential Google Colaboratory Tips & Tricks - Feb 12, 2018.
Google Colaboratory is a promising machine learning research platform. Here are 3 tips to simplify its usage and facilitate using a GPU, installing libraries, and uploading data files.
Google, Google Colab, Python, TensorFlow, Tips
- Gradient Boosting in TensorFlow vs XGBoost - Jan 18, 2018.
For many Kaggle-style data mining problems, XGBoost has been the go-to solution since its release in 2016. It's probably as close to an out-of-the-box machine learning algorithm as you can get today.
Gradient Boosting, Python, TensorFlow, XGBoost
A Day in the Life of an AI Developer - Jan 16, 2018.
This is the narrative of a typical AI Sunday, where I decided to look at building a sequence to sequence (seq2seq) model based chatbot using some already available sample code and data from the Cornell movie database.
AI, Developer, TensorFlow
- Custom Optimizer in TensorFlow - Jan 8, 2018.
How to customize the optimizers to speed-up and improve the process of finding a (local) minimum of the loss function using TensorFlow.
Deep Learning, Optimization, TensorFlow
- Deep Learning Made Easy with Deep Cognition - Dec 21, 2017.
So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.
Pages: 1 2
Cloud, Deep Learning, Keras, Neural Networks, TensorFlow
- Getting Started with TensorFlow: A Machine Learning Tutorial - Dec 19, 2017.
A complete and rigorous introduction to Tensorflow. Code along with this tutorial to get started with hands-on examples.
Pages: 1 2
Machine Learning, Python, TensorFlow
- TensorFlow for Short-Term Stocks Prediction - Dec 12, 2017.
In this post you will see an application of Convolutional Neural Networks to stock market prediction, using a combination of stock prices with sentiment analysis.
Convolutional Neural Networks, Finance, Python, Stocks, TensorFlow
- Exploring Recurrent Neural Networks - Dec 1, 2017.
We explore recurrent neural networks, starting with the basics, using a motivating weather modeling problem, and implement and train an RNN in TensorFlow.
Neural Networks, Packt Publishing, Python, Recurrent Neural Networks, TensorFlow
Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras - Nov 29, 2017.
We show how to build a deep neural network that classifies images to many categories with an accuracy of a 90%. This was a very hard problem before the rise of deep networks and especially Convolutional Neural Networks.
Pages: 1 2
Convolutional Neural Networks, Deep Learning, Keras, TensorFlow
- How To Unit Test Machine Learning Code - Nov 28, 2017.
One of the main principles I learned during my time at Google Brain was that unit tests can make or break your algorithm and can save you weeks of debugging and training time.
Machine Learning, Neural Networks, Python, Software Engineering, TensorFlow
- Using TensorFlow for Predictive Analytics with Linear Regression - Nov 21, 2017.
This post presents a powerful and simple example of how to use TensorFlow to perform a Linear Regression. check out the code for your own experiments!
Linear Regression, TensorFlow
- Top 10 Videos on Deep Learning in Python - Nov 17, 2017.
Playlists, individual tutorials (not part of a playlist) and online courses on Deep Learning (DL) in Python using the Keras, Theano, TensorFlow and PyTorch libraries. Assumes no prior knowledge. These videos cover all skill levels and time constraints!
Deep Learning, Keras, Python, PyTorch, TensorFlow, Theano, Top 10, Tutorials, Videolectures, Youtube
- TensorFlow: What Parameters to Optimize? - Nov 9, 2017.
Learning TensorFlow Core API, which is the lowest level API in TensorFlow, is a very good step for starting learning TensorFlow because it let you understand the kernel of the library. Here is a very simple example of TensorFlow Core API in which we create and train a linear regression model.
Neural Networks, Optimization, Python, TensorFlow
Ranking Popular Deep Learning Libraries for Data Science - Oct 23, 2017.
We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
Caffe, Deep Learning, Keras, Python, PyTorch, TensorFlow, Theano
TensorFlow: Building Feed-Forward Neural Networks Step-by-Step - Oct 23, 2017.
This article will take you through all steps required to build a simple feed-forward neural network in TensorFlow by explaining each step in details.
Pages: 1 2 3
Deep Learning, Neural Networks, TensorFlow
- Data Science –The need for a Systems Engineering approach - Oct 5, 2017.
We need a greater emphasis on the Systems Engineering aspects of Data Science. I am exploring these ideas as part of my course "Data Science for Internet of Things" at the University of Oxford.
Data Science, Oxford, Systems Engineering, TensorFlow
- Tensorflow Tutorial, Part 2 – Getting Started - Sep 28, 2017.
This tutorial will lay a solid foundation to your understanding of Tensorflow, the leading Deep Learning platform. The second part shows how to get started, install, and build a small test case.
Deep Learning, GPU, Python, TensorFlow
- PyTorch or TensorFlow? - Aug 29, 2017.
PyTorch is better for rapid prototyping in research, for hobbyists and for small scale projects. TensorFlow is better for large-scale deployments, especially when cross-platform and embedded deployment is a consideration.
Deep Learning, Neural Networks, PyTorch, TensorFlow
The world’s first protein database for Machine Learning and AI - Jun 22, 2017.
dSPP is the world first interactive database of proteins for AI and Machine Learning, and is fully integrated with Keras and Tensorflow. You can access the database at peptone.io/dspp
Bioinformatics, Genomics, Keras, Machine Learning, Protein, TensorFlow
- Deep Learning: TensorFlow Programming via XML and PMML - Jun 9, 2017.
In this approach, problem dataset and its Neural network are specified in a PMML like XML file. Then it is used to populate the TensorFlow graph, which, in turn run to get the results.
Deep Learning, PMML, TensorFlow
- Deep Learning 101: Demystifying Tensors - Jun 2, 2017.
Many deep-learning systems available today are based on tensor algebra, but tensor algebra isn’t tied to deep-learning. It isn’t hard to get started with tensor abuse but can be hard to stop.
Deep Learning, Tensor, TensorFlow
New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll - May 22, 2017.
Python caught up with R and (barely) overtook it; Deep Learning usage surges to 32%; RapidMiner remains top general Data Science platform; Five languages of Data Science.
Pages: 1 2
Anaconda, Data Mining Software, Poll, Python, R, RapidMiner, Spark, TensorFlow
- How Not To Program the TensorFlow Graph - May 1, 2017.
Using TensorFlow from Python is like using Python to program another computer. Being thoughtful about the graphs you construct can help you avoid confusion and costly performance problems.
Deep Learning, Programming, Python, TensorFlow
- How to Build a Recurrent Neural Network in TensorFlow - Apr 26, 2017.
This is a no-nonsense overview of implementing a recurrent neural network (RNN) in TensorFlow. Both theory and practice are covered concisely, and the end result is running TensorFlow RNN code.
Deep Learning, Neural Networks, Recurrent Neural Networks, TensorFlow
- Getting Started with Deep Learning - Mar 24, 2017.
This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.
Caffe, CNTK, Deep Learning, Keras, SVDS, TensorFlow, Theano, Torch
An Overview of Python Deep Learning Frameworks - Feb 27, 2017.
Read this concise overview of leading Python deep learning frameworks, including Theano, Lasagne, Blocks, TensorFlow, Keras, MXNet, and PyTorch.
Deep Learning, Keras, Neural Networks, Python, TensorFlow, Theano, Torch
- Implementing a CNN for Human Activity Recognition in Tensorflow - Nov 21, 2016.
In this post, we will see how to employ Convolutional Neural Network (CNN) for HAR, that will learn complex features automatically from the raw accelerometer signal to differentiate between different activities of daily life.
Pages: 1 2
Convolutional Neural Networks, Deep Learning, TensorFlow, Time Series Classification
- Introduction to Trainspotting: Computer Vision, Caltrain, and Predictive Analytics - Nov 1, 2016.
We previously analyzed delays using Caltrain’s real-time API to improve arrival predictions, and we have modeled the sounds of passing trains to tell them apart. In this post we’ll start looking at the nuts and bolts of making our Caltrain work possible.
Computer Vision, Raspberry Pi, SVDS, TensorFlow
- MLDB: The Machine Learning Database - Oct 17, 2016.
MLDB is an opensource database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.
Classification, Database, Machine Learning, TensorFlow, Transfer Learning
- Urban Sound Classification with Neural Networks in Tensorflow - Sep 12, 2016.
This post discuss techniques of feature extraction from sound in Python using open source library Librosa and implements a Neural Network in Tensorflow to categories urban sounds, including car horns, children playing, dogs bark, and more.
Pages: 1 2
Deep Learning, Feature Extraction, Machine Learning, Neural Networks, TensorFlow
- The Gentlest Introduction to Tensorflow – Part 2 - Aug 19, 2016.
Check out the second and final part of this introductory tutorial to TensorFlow.
Pages: 1 2
Beginners, Deep Learning, Gradient Descent, Machine Learning, TensorFlow
- Multi-Task Learning in Tensorflow: Part 1 - Jul 20, 2016.
A discussion and step-by-step tutorial on how to use Tensorflow graphs for multi-task learning.
Pages: 1 2
Machine Learning, Neural Networks, TensorFlow
- Recursive (not Recurrent!) Neural Networks in TensorFlow - Jun 30, 2016.
Learn how to implement recursive neural networks in TensorFlow, which can be used to learn tree-like structures, or directed acyclic graphs.
Neural Networks, TensorFlow
- Top 10 IPython Notebook Tutorials for Data Science and Machine Learning - Apr 22, 2016.
A list of 10 useful Github repositories made up of IPython (Jupyter) notebooks, focused on teaching data science and machine learning. Python is the clear target here, but general principles are transferable.
Data Science, Deep Learning, GitHub, IPython, Machine Learning, Python, Sebastian Raschka, TensorFlow
- Distributed TensorFlow Has Arrived - Mar 1, 2016.
Google has open sourced its distributed version of TensorFlow. Get the info on it here, and catch up on some other TensorFlow news at the same time.
Deep Learning, Distributed Systems, Google, Matthew Mayo, TensorFlow
- Opening Up Deep Learning For Everyone - Feb 19, 2016.
Opening deep learning up to everyone is a noble goal. But is it achievable? Should non-programmers and even non-technical people be able to implement deep neural models?
Caffe, Deep Learning, Feature Engineering, Open Source, TensorFlow
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn - Feb 12, 2016.
Scikit Learn is a new easy-to-use interface for TensorFlow from Google based on the Scikit-learn fit/predict model. Does it succeed in making deep learning more accessible?
Deep Learning, Google, Matthew Mayo, Python, scikit-learn, TensorFlow
- Deep Learning with Spark and TensorFlow - Jan 28, 2016.
The integration of TensorFlow with Spark leverages the distributed framework for hyperparameter tuning and model deployment at scale. Both time savings and improved error rates are demonstrated.
Apache Spark, Deep Learning, Distributed Systems, TensorFlow
- Google Launches Deep Learning with TensorFlow MOOC - Jan 26, 2016.
Google and Udacity have partnered for a new self-paced course on deep learning and TensorFlow, starting immediately.
Google, Matthew Mayo, MOOC, TensorFlow, Udacity
- 7 Steps to Understanding Deep Learning - Jan 11, 2016.
There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!
Pages: 1 2
7 Steps, Caffe, Convolutional Neural Networks, Deep Learning, Matthew Mayo, Recurrent Neural Networks, TensorFlow, Theano
- Top KDnuggets tweets, Nov 16-22: Dilbert discovers the perfect chart; TensorFlow Disappoints – Google Deep Learning falls shallow - Nov 23, 2015.
A standard #graph for any occasion! #Dilbert discovers the perfect chart; TensorFlow Disappoints - Google #DeepLearning falls shallow; All the #BigData tools and how to use them; KDnuggets #DataScience #Cartoon Caption Contest.
Cartoon, Deep Learning, Dilbert, James Bond, TensorFlow, Tesla
