- KDnuggets™ News 21:n40, Oct 20: The 20 Python Packages You Need For Machine Learning and Data Science; Ace Data Science Interviews with Portfolio Projects - Oct 20, 2021.
The 20 Python Packages You Need For Machine Learning and Data Science; How to Ace Data Science Interview by Working on Portfolio Projects; Deploying Your First Machine Learning API; Real Time Image Segmentation Using 5 Lines of Code; What is Clustering and How Does it Work?
Clustering, Computer Vision, Data Science, Image Recognition, Interview, Machine Learning, Portfolio, Python
- Multilingual CLIP with Huggingface + PyTorch Lightning - Mar 26, 2021.
An overview of training OpenAI's CLIP on Google Colab.
CLIP, Google Colab, Hugging Face, Image Recognition, NLP, OpenAI, PyTorch, PyTorch Lightning
Deep learning doesn’t need to be a black box - Feb 5, 2021.
The cultural perception of AI is often suspect because of the described challenges in knowing why a deep neural network makes its predictions. So, researchers try to crack open this "black box" after a network is trained to correlate results with inputs. But, what if the goal of explainability could be designed into the network's architecture -- before the model is trained and without reducing its predictive power? Maybe the box could stay open from the beginning.
Convolutional Neural Networks, Deep Learning, Explainability, Explainable AI, Image Recognition
- Support Vector Machine for Hand Written Alphabet Recognition in R - Jan 27, 2021.
We attempt to break down a problem of hand written alphabet image recognition into a simple process rather than using heavy packages. This is an attempt to create the data and then build a model using Support Vector Machines for Classification.
Classification, Image Recognition, Machine Learning, R, Support Vector Machines
Building a Deep Learning Based Reverse Image Search - Jan 22, 2021.
Following the journey from unstructured data to content based image retrieval.
Deep Learning, Image Recognition, Search
- Build Dog Breeds Classifier Step By Step with AWS Sagemaker - Jun 17, 2020.
This post takes you through the basic steps for creating a cloud-based deep learning dog classifier, with everything accomplished from the AWS Management Console.
AWS, Dogs, Image Classification, Image Recognition, Sagemaker
Deep Learning for Detecting Pneumonia from X-ray Images - Jun 5, 2020.
This article covers an end to end pipeline for pneumonia detection from X-ray images.
Deep Learning, Healthcare, Image Recognition, Python
- 5 Machine Learning Papers on Face Recognition - May 28, 2020.
This article will highlight some of that research and introduce five machine learning papers on face recognition.
Face Recognition, Image Recognition, Machine Learning, Neural Networks
- Interactive Machine Learning Experiments - May 26, 2020.
Dive into experimenting with machine learning techniques using this open-source collection of interactive demos built on multilayer perceptrons, convolutional neural networks, and recurrent neural networks. Each package consists of ready-to-try web browser interfaces and fully-developed notebooks for you to fine tune the training for better performance.
Convolutional Neural Networks, GitHub, Image Recognition, Jupyter, Machine Learning, Recurrent Neural Networks, Tutorials
- Google Open Sources SimCLR, A Framework for Self-Supervised and Semi-Supervised Image Training - Apr 27, 2020.
The new framework uses contrastive learning to improve image analysis in unlabeled datasets.
Google, Image Recognition, Open Source, Self-supervised Learning
- Image Recognition and Object Detection in Retail - Feb 26, 2020.
“According to Gartner, by 2020, 85% of customer interactions in the retail industry will be managed by AI.”
Image Recognition, Object Detection, Retail
- 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
- This Microsoft Neural Network can Answer Questions About Scenic Images with Minimum Training - Oct 21, 2019.
Recently, a group of AI experts from Microsoft Research published a paper proposing a method for scene understanding that combines two key tasks: image captioning and visual question answering (VQA).
Image Recognition, Microsoft, Neural Networks, Question answering, Training
- 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
- A 2019 Guide to Human Pose Estimation - Aug 28, 2019.
Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.
AI, Computer Vision, Image Recognition, Video recognition
- A 2019 Guide to Semantic Segmentation - Aug 12, 2019.
Semantic segmentation refers to the process of linking each pixel in an image to a class label. These labels could include a person, car, flower, piece of furniture, etc., just to mention a few. We’ll now look at a number of research papers on covering state-of-the-art approaches to building semantic segmentation models.
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Image Classification, Image Recognition, Python, Segmentation
- Introduction to Image Segmentation with K-Means clustering - Aug 9, 2019.
Image segmentation is the classification of an image into different groups. Many kinds of research have been done in the area of image segmentation using clustering. In this article, we will explore using the K-Means clustering algorithm to read an image and cluster different regions of the image.
Clustering, Computer Vision, Image Recognition, K-means, Python, Segmentation
- A 2019 Guide to Object Detection - Aug 1, 2019.
Object detection has been applied widely in video surveillance, self-driving cars, and object/people tracking. In this piece, we’ll look at the basics of object detection and review some of the most commonly-used algorithms and a few brand new approaches, as well.
Computer Vision, Image Recognition, Object Detection
- An Overview of Human Pose Estimation with Deep Learning - Jun 28, 2019.
Human Pose Estimation is one of the main research areas in computer vision. The reason for its importance is the abundance of applications that can benefit from such a technology. Here's an introduction to the different techniques used in Human Pose Estimation based on Deep Learning.
Computer Vision, Convolutional Neural Networks, Deep Learning, Image Recognition, Object Detection
- K-means Clustering with Dask: Image Filters for Cat Pictures - Jun 18, 2019.
How to recreate an original cat image with least possible colors. An interesting use case of Unsupervised Machine Learning with K Means Clustering in Python.
Clustering, Dask, Image Classification, Image Recognition, K-means, Python, Unsupervised Learning
- Boost Your Image Classification Model - May 27, 2019.
Check out this collection of tricks to improve the accuracy of your classifier.
fast.ai, Generative Adversarial Network, Image Classification, Image Recognition, Python
- Object Detection with Luminoth - Mar 13, 2019.
In this article you will learn about Luminoth, an open source computer vision library which sits atop Sonnet and TensorFlow and provides object detection for images and video.
Computer Vision, Image Recognition, Object Detection, Python
- People Tracking using Deep Learning - Mar 12, 2019.
Read this overview of people tracking and how deep learning-powered computer vision has allowed for phenomenal performance.
Deep Learning, Image Recognition, Object Detection
- How to do Everything in Computer Vision - Feb 27, 2019.
The many standard tasks in computer vision all require special consideration: classification, detection, segmentation, pose estimation, enhancement and restoration, and action recognition. Let me show you how to do everything in Computer Vision with Deep Learning!
Computer Vision, Convolutional Neural Networks, Image Classification, Image Recognition, Neural Networks, Object Detection
- Building an image search service from scratch - Jan 30, 2019.
By the end of this post, you should be able to build a quick semantic search model from scratch, no matter the size of your dataset.
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Computer Vision, Image Recognition, NLP, Search, Search Engine, Word Embeddings
- Deep learning in Satellite imagery - Dec 26, 2018.
This article outlines possible sources of satellite imagery, what its properties are and how this data can be utilised using R.
Deep Learning, Image Recognition, R
- 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
- Building an Image Classifier Running on Raspberry Pi - Oct 9, 2018.
The tutorial starts by building the Physical network connecting Raspberry Pi to the PC via a router. After preparing their IPv4 addresses, SSH session is created for remotely accessing of the Raspberry Pi. After uploading the classification project using FTP, clients can access it using web browsers for classifying images.
Pages: 1 2
Classifier, Image Recognition, Raspberry Pi
- Semantic Segmentation: Wiki, Applications and Resources - Oct 4, 2018.
An extensive overview covering the features of Semantic Segmentation and possible uses for it, including GeoSensing, Autonomous Drive, Facial Recognition and more.
Deep Learning, Image Recognition, Machine Learning, Object Detection, Segmentation
- Data Capture – the Deep Learning Way - Sep 21, 2018.
An overview of how an information extraction pipeline built from scratch on top of deep learning inspired by computer vision can shakeup the established field of OCR and data capture.
Deep Learning, Image Recognition
- Data Augmentation For Bounding Boxes: Rethinking image transforms for object detection - Sep 19, 2018.
Data Augmentation is one way to battle this shortage of data, by artificially augmenting our dataset. In fact, the technique has proven to be so successful that it's become a staple of deep learning systems.
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Deep Learning, Image Recognition, Neural Networks, Object Detection, Python
- Object Detection and Image Classification with YOLO - Sep 10, 2018.
We explain object detection, how YOLO algorithm can help with image classification, and introduce the open source neural network framework Darknet.
Image Recognition, Object Detection, YOLO
- How GOAT Taught a Machine to Love Sneakers - Aug 7, 2018.
Embeddings are a fantastic tool to create reusable value with inherent properties similar to how humans interpret objects. GOAT uses deep learning to generate these for their entire sneaker catalogue.
Autoencoder, Deep Learning, Image Recognition, Word Embeddings
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
How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1 - May 17, 2018.
The best way to go about learning object detection is to implement the algorithms by yourself, from scratch. This is exactly what we'll do in this tutorial.
Computer Vision, Image Recognition, Neural Networks, Object Detection, Python, PyTorch, YOLO
- How to Organize Data Labeling for Machine Learning: Approaches and Tools - May 16, 2018.
The main challenge for a data science team is to decide who will be responsible for labeling, estimate how much time it will take, and what tools are better to use.
Pages: 1 2
Altexsoft, Crowdsourcing, Data Labeling, Data Preparation, Image Recognition, Machine Learning, Training Data
50+ Useful Machine Learning & Prediction APIs, 2018 Edition - May 1, 2018.
Extensive list of 50+ APIs in Face and Image Recognition ,Text Analysis, NLP, Sentiment Analysis, Language Translation, Machine Learning and prediction.
API, Face Recognition, Image Recognition, Machine Learning, Natural Language Processing, Sentiment Analysis, Text Analytics
Building Convolutional Neural Network using NumPy from Scratch - Apr 26, 2018.
In this article, CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), ReLU, and max pooling.
Convolutional Neural Networks, Image Recognition, Neural Networks, numpy, Python
- 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
Exploring DeepFakes - Mar 27, 2018.
In this post, I explore the capabilities of this tech, describe how it works, and discuss potential applications.
Pages: 1 2
Deep Learning, Image Recognition, Video recognition
- 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
- Visual Aesthetics: Judging photo quality using AI techniques - Jan 18, 2018.
We built a deep learning system that can automatically analyze and score an image for aesthetic quality with high accuracy. Check the demo and see your photo measures up!
AI, Deep Learning, Image Recognition
- Detecting Facial Features Using Deep Learning - Sep 4, 2017.
A challenging task in the past was detection of faces and their features like eyes, nose, mouth and even deriving emotions from their shapes. This task can be now “magically” solved by deep learning and any talented teenager can do it in a few hours.
Convolutional Neural Networks, Deep Learning, Image Recognition, Neural Networks
- Using AI to Super Compress Images - Aug 21, 2017.
Neural Network algorithms are showing promising results for different complex problems. Here we discuss how these algorithms are used in image compression.
AI, Compression, Convolutional Neural Networks, Image Recognition
A Guide to Instagramming with Python for Data Analysis - Aug 17, 2017.
I am writing this article to show you the basics of using Instagram in a programmatic way. You can benefit from this if you want to use it in a data analysis, computer vision, or any other cool project you can think of.
Pages: 1 2
Data Analysis, Image Recognition, Instagram, Python
- 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
- How Convolutional Neural Networks Accomplish Image Recognition? - Aug 9, 2017.
Image recognition is very interesting and challenging field of study. Here we explain concepts, applications and techniques of image recognition using Convolutional Neural Networks.
Clarifai, Convolutional Neural Networks, IBM Watson, Image Recognition, Neural Networks
- Data preprocessing for deep learning with nuts-ml - May 30, 2017.
Nuts-ml is a new data pre-processing library in Python for GPU-based deep learning in vision. It provides common pre-processing functions as independent, reusable units. These so called ‘nuts’ can be freely arranged to build data flows that are efficient, easy to read and modify.
Data Preparation, Deep Learning, IBM, Image Recognition, Python
- What Data You Analyzed – KDnuggets Poll Results and Trends - Apr 26, 2017.
Image/video data analysis is surging, JSON replacing XML, anonymized data usage is growing in US and Europe (but not in Asia), itemsets and Twitter analysis is declining - some of the highlights of KDnuggets Poll on data types used.
Anonymized, Asia, Data types, Europe, Image Recognition, Poll, Text Analysis, Time Series, USA
- Artificial Neural Networks (ANN) Introduction, Part 1 - Dec 8, 2016.
This intro to ANNs will look at how we can train an algorithm to recognize images of handwritten digits. We will be using the images from the famous MNIST (Mixed National Institute of Standards and Technology) database.
Algobeans, Image Recognition, MNIST, Neural Networks
- Top /r/MachineLearning Posts, October: NSFW Image Recognition, Differentiable Neural Computers, Hinton on Coursera - Nov 4, 2016.
NSFW Image Recognition, Differentiable Neural Computers, Hinton's Neural Networks for Machine Learning Coursera course; Introducing the AI Open Network; Making a Self-driving RC Car
DeepMind, Geoff Hinton, Image Recognition, Machine Learning, Neural Networks, Reddit, Self-Driving Car
- Deep Learning Reading Group: Deep Residual Learning for Image Recognition - Sep 22, 2016.
Published in 2015, today's paper offers a new architecture for Convolution Networks, one which has since become a staple in neural network implementation. Read all about it here.
Academics, Convolutional Neural Networks, Deep Learning, Image Recognition, Lab41, Machine Learning, Neural Networks
- How Convolutional Neural Networks Work - Aug 31, 2016.
Get an overview of what is going on inside convolutional neural networks, and what it is that makes them so effective.
Pages: 1 2
Brandon Rohrer, Convolutional Neural Networks, Image Recognition, Neural Networks
- 50 Useful Machine Learning & Prediction APIs - Dec 7, 2015.
We present a list of 50 APIs selected from areas like machine learning, prediction, text analytics & classification, face recognition, language translation etc. Start consuming APIs!
Pages: 1 2
API, Data Science, Face Recognition, IBM Watson, Image Recognition, Machine Learning, NLP, Sentiment Analysis
- MetaMind Mastermind Richard Socher: Uncut Interview - Oct 20, 2015.
In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.
Convolutional Neural Networks, Deep Learning, Image Recognition, MetaMind, Recurrent Neural Networks, Richard Socher, Zachary Lipton
- Recycling Deep Learning Models with Transfer Learning - Aug 14, 2015.
Deep learning exploits gigantic datasets to produce powerful models. But what can we do when our datasets are comparatively small? Transfer learning by fine-tuning deep nets offers a way to leverage existing datasets to perform well on new tasks.
Deep Learning, Image Recognition, ImageNet, Machine Learning, Neural Networks, Transfer Learning, Zachary Lipton
- Deep Learning, The Curse of Dimensionality, and Autoencoders - Mar 12, 2015.
Autoencoders are an extremely exciting new approach to unsupervised learning and for many machine learning tasks they have already surpassed the decades of progress made by researchers handpicking features.
Pages: 1 2 3
Autoencoder, Deep Learning, Face Recognition, Geoff Hinton, Image Recognition, Nikhil Buduma
- Tinderbox: Automating Romance with Tinder and Eigenfaces - Feb 15, 2015.
Tinderbox is a software uses machine learning and image recognition to automate Tinder, a popular app for single meetings. The author describes his experience and feedback until it started to work too well.
Bots, Eigenface, Image Recognition, Romance, Tinder
- Deep Learning can be easily fooled - Jan 14, 2015.
It is almost impossible for human eyes to label the images below to be anything but abstract arts. However, researchers found that Deep Neural Network will label them to be familiar objects with 99.99% confidence. The generality of DNN is questioned again.
Deep Learning, Deep Neural Network, Evolutionary Algorithm, Image Recognition, Ran Bi
- Deep Learning – important resources for learning and understanding - Aug 21, 2014.
New and fundamental resources for learning about Deep Learning - the hottest machine learning method, which is approaching human performance level.
Deep Learning, Image Recognition, Machine Learning, Yann LeCun, Yoshua Bengio
- Does Deep Learning Have Deep Flaws? - Jun 19, 2014.
A recent study of neural networks found that for every correctly classified image, one can generate an "adversarial", visually indistinguishable image that will be misclassified. This suggests potential deep flaws in all neural networks, including possibly a human brain.
Artificial Intelligence, Deep Learning, Google, Image Recognition, Neural Networks
