- Multivariate Time Series Analysis with an LSTM based RNN - Oct 29, 2021.
Check out this codeless solution using the Keras integration.
Keras, Knime, Low-Code, LSTM, Time Series
- 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
- 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
- Build Your First Data Science Application - Feb 4, 2021.
Check out these seven Python libraries to make your first data science MVP application.
API, Data Science, Jupyter, Keras, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn
- Working With The Lambda Layer in Keras - Jan 28, 2021.
In this tutorial we'll cover how to use the Lambda layer in Keras to build, save, and load models which perform custom operations on your data.
Architecture, Keras, Neural Networks, Python
- 5 Tools for Effortless Data Science - Jan 11, 2021.
The sixth tool is coffee.
Data Science, Data Science Tools, Keras, Machine Learning, MLflow, PyCaret, Python
- How to Create Custom Real-time Plots in Deep Learning - Dec 14, 2020.
How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.
Data Visualization, Deep Learning, Keras, Metrics, Neural Networks, Python
- 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
- 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
- Introduction to Convolutional Neural Networks - Jun 3, 2020.
The article focuses on explaining key components in CNN and its implementation using Keras python library.
Convolutional Neural Networks, Keras, Neural Networks, Python
- Build PyTorch Models Easily Using torchlayers - Apr 9, 2020.
torchlayers aims to do what Keras did for TensorFlow, providing a higher-level model-building API and some handy defaults and add-ons useful for crafting PyTorch neural networks.
API, Keras, Neural Networks, Python, PyTorch
- 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
- Hands on Hyperparameter Tuning with Keras Tuner - Feb 28, 2020.
Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.
Automated Machine Learning, AutoML, Keras, Python
- 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
- Fighting Overfitting in Deep Learning - Dec 27, 2019.
This post outlines an attack plan for fighting overfitting in neural networks.
Deep Learning, Keras, Neural Networks, Overfitting, Python, Regularization, Transfer Learning
- Automated Machine Learning Project Implementation Complexities - Nov 22, 2019.
To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.
Automated Machine Learning, Keras, Pipeline, Python
- 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
- Writing Your First Neural Net in Less Than 30 Lines of Code with Keras - Oct 18, 2019.
Read this quick overview of neural networks and learn how to implement your first in very few lines using Keras.
Keras, Neural Networks, Python
- A Single Function to Streamline Image Classification with Keras - Sep 23, 2019.
We show, step-by-step, how to construct a single, generalized, utility function to pull images automatically from a directory and train a convolutional neural net model.
Image Classification, Image Recognition, Keras, Python
- 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
- Deep Learning for NLP: Creating a Chatbot with Keras! - Aug 19, 2019.
Learn how to use Keras to build a Recurrent Neural Network and create a Chatbot! Who doesn’t like a friendly-robotic personal assistant?
Chatbot, Deep Learning, Keras, NLP, Python
- Keras Callbacks Explained In Three Minutes - Aug 9, 2019.
A gentle introduction to callbacks in Keras. Learn about EarlyStopping, ModelCheckpoint, and other callback functions with code examples.
Explained, Keras, Neural Networks, Python
- How a simple mix of object-oriented programming can sharpen your deep learning prototype - Aug 1, 2019.
By mixing simple concepts of object-oriented programming, like functionalization and class inheritance, you can add immense value to a deep learning prototyping code.
Deep Learning, Keras, Programming, Python
- 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
- 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
- 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
- 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
- Pedestrian Detection in Aerial Images Using RetinaNet - Mar 26, 2019.
Object Detection in Aerial Images is a challenging and interesting problem. By using Keras to train a RetinaNet model for object detection in aerial images, we can use it to extract valuable information.
AI, Computer Vision, Deep Learning, Keras, Object Detection, Retina Net
- 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
- 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
- Automated Machine Learning in Python - Jan 18, 2019.
An organization can also reduce the cost of hiring many experts by applying AutoML in their data pipeline. AutoML also reduces the amount of time it would take to develop and test a machine learning model.
Automated Machine Learning, AutoML, H2O, Keras, Machine Learning, Python, scikit-learn
- The 6 Most Useful Machine Learning Projects of 2018 - Jan 15, 2019.
Let’s take a look at the top 6 most practically useful ML projects over the past year. These projects have published code and datasets that allow individual developers and smaller teams to learn and immediately create value.
Automated Machine Learning, Facebook, fast.ai, Google, Keras, Machine Learning, Object Detection, Python, Reinforcement Learning, Word Embeddings
- Solve any Image Classification Problem Quickly and Easily - Dec 13, 2018.
This article teaches you how to use transfer learning to solve image classification problems. A practical example using Keras and its pre-trained models is given for demonstration purposes.
Pages: 1 2
Classification, Computer Vision, Image Recognition, Keras, Python
- Keras Hyperparameter Tuning in Google Colab Using Hyperas - Dec 12, 2018.
In this post, I will show you how you can tune the hyperparameters of your existing keras models using Hyperas and run everything in a Google Colab Notebook.
Automated Machine Learning, Google, Google Colab, Hyperparameter, Keras, Python
- Handling Imbalanced Datasets in Deep Learning - Dec 4, 2018.
It’s important to understand why we should do it so that we can be sure it’s a valuable investment. Class balancing techniques are only really necessary when we actually care about the minority classes.
Balancing Classes, Datasets, Deep Learning, Keras, Python
- Using a Keras Long Short-Term Memory (LSTM) Model to Predict Stock Prices - Nov 21, 2018.
LSTMs are very powerful in sequence prediction problems because they’re able to store past information. This is important in our case because the previous price of a stock is crucial in predicting its future price.
Finance, Keras, LSTM, Neural Networks, Stocks
- Introduction to Deep Learning with Keras - Oct 29, 2018.
In this article, we’ll build a simple neural network using Keras. Now let’s proceed to solve a real business problem: an insurance company wants you to develop a model to help them predict which claims look fraudulent.
Pages: 1 2
Deep Learning, Keras, Neural Networks, Python
- Top 8 Python Machine Learning Libraries - Oct 9, 2018.
Part 1 of a new series investigating the top Python Libraries across Machine Learning, AI, Deep Learning and Data Science.
GitHub, Keras, Machine Learning, Python
- 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
- Don’t Use Dropout in Convolutional Networks - Sep 5, 2018.
If you are wondering how to implement dropout, here is your answer - including an explanation on when to use dropout, an implementation example with Keras, batch normalization, and more.
Convolutional Neural Networks, Dropout, Keras
- 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
- Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code - Aug 17, 2018.
Auto-Keras is an open source software library for automated machine learning. Auto-Keras provides functions to automatically search for architecture and hyperparameters of deep learning models.
Automated Machine Learning, Keras, Neural Networks, Python
- Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors - Jul 5, 2018.
In this tutorial, I classify Yelp round-10 review datasets. After processing the review comments, I trained three model in three different ways and obtained three word embeddings.
Convolutional Neural Networks, Keras, LSTM, NLP, Python, Text Classification, Word Embeddings
- Deep Quantile Regression - Jul 3, 2018.
Most Deep Learning frameworks currently focus on giving a best estimate as defined by a loss function. Occasionally something beyond a point estimate is required to make a decision. This is where a distribution would be useful. This article will purely focus on inferring quantiles.
Deep Learning, Hyperparameter, Keras, Neural Networks, Python, Regression
- Building a Basic Keras Neural Network Sequential Model - Jun 29, 2018.
The approach basically coincides with Chollet's Keras 4 step workflow, which he outlines in his book "Deep Learning with Python," using the MNIST dataset, and the model built is a Sequential network of Dense layers. A building block for additional posts.
Keras, MNIST, Neural Networks, Python
- 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
- 5 Machine Learning Projects You Should Not Overlook, June 2018 - Jun 12, 2018.
Here is a new installment of 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out!
Interpretability, Keras, Machine Learning, Model Performance, NLP, Overlook, Recurrent Neural Networks, Visualization
- 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
- The Keras 4 Step Workflow - Jun 4, 2018.
In his book "Deep Learning with Python," Francois Chollet outlines a process for developing neural networks with Keras in 4 steps. Let's take a look at this process with a simple example.
Francois Chollet, Keras, Neural Networks, Python, Workflow
- 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
- 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
- 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
- 5 Fantastic Practical Natural Language Processing Resources - Feb 22, 2018.
This post presents 5 practical resources for getting a start in natural language processing, covering a wide array of topics and approaches.
Deep Learning, Keras, LSTM, Neural Networks, NLP, NLTK, Python
- 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
- 5 Machine Learning Projects You Should Not Overlook - Feb 8, 2018.
It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out!
Bayesian, Gradient Boosting, Keras, Machine Learning, Overlook, PHP, Python, scikit-learn
- Using Genetic Algorithm for Optimizing Recurrent Neural Networks - Jan 22, 2018.
In this tutorial, we will see how to apply a Genetic Algorithm (GA) for finding an optimal window size and a number of units in Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN).
Automated Machine Learning, Genetic Algorithm, Keras, Neural Networks, Python, Recurrent Neural Networks
- 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
- Today I Built a Neural Network During My Lunch Break with Keras - Dec 8, 2017.
So yesterday someone told me you can build a (deep) neural network in 15 minutes in Keras. Of course, I didn’t believe that at all. So the next day I set out to play with Keras on my own data.
Keras, Neural Networks, Python
- 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
- 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
- 7 Steps to Mastering Deep Learning with Keras - Oct 30, 2017.
Are you interested in learning how to use Keras? Do you already have an understanding of how neural networks work? Check out this lean, fat-free 7 step plan for going from Keras newbie to master of its basics as quickly as is possible.
7 Steps, Convolutional Neural Networks, Deep Learning, Keras, Logistic Regression, LSTM, Machine Learning, Neural Networks, Python, Recurrent Neural Networks
- 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
- Keras Tutorial: Recognizing Tic-Tac-Toe Winners with Neural Networks - Sep 18, 2017.
In this tutorial, we will build a neural network with Keras to determine whether or not tic-tac-toe games have been won by player X for given endgame board configurations. Introductory neural network concerns are covered.
Games, Keras, Neural Networks, Python
- An Intuitive Guide to Deep Network Architectures - Aug 28, 2017.
How and why do different Deep Learning models work? We provide an intuitive explanation for 3 very popular DL models: Resnet, Inception, and Xception.
Pages: 1 2
Deep Learning, Keras, Neural Networks
- First Steps of Learning Deep Learning: Image Classification in Keras - Aug 16, 2017.
Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over, this post is for you!
Pages: 1 2
Deep Learning, Image Recognition, Keras, Neural Networks
- Deep Learning with R + Keras - Jun 27, 2017.
Keras has grown in popularity and supported on a wide set of platforms including Tensorflow, CNTK, Apple’s CoreML, and Theano. It is becoming the de factor language for deep learning.
Deep Learning, Keras, Neural Networks, R
- 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
- 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
- MNIST Generative Adversarial Model in Keras - Jul 19, 2016.
This post discusses and demonstrates the implementation of a generative adversarial network in Keras, using the MNIST dataset.
GANs, Generative Models, Keras, MNIST