- Top 7 Open Source OCR Models
Best OCR and vision language models you can run locally that transform documents, tables, and diagrams into flawless markdown copies with benchmark-crushing accuracy.
Computer Vision
- 7 Computer Vision Projects for All Levels
Each project, from beginner tasks like Image Classification to advanced ones like Anomaly Detection, includes a link to the dataset and source code for easy access and implementation.
Computer Vision
- 10 GitHub Repositories to Master Computer Vision
The GitHub repository includes up-to-date learning resources, research papers, guides, popular tools, tutorials, projects, and datasets.
Computer Vision
- An Overview of Hugging Face Diffusers
Getting Started with HuggingFace Diffusers: A Beginner's Journey into the World of Generative Images
Computer Vision
- Closed Source VS Open Source Image Annotation
This blog strikes a comparison between open-source and closed-source image annotation tools and how it makes the life of AI model developers easy and convenient.
Computer Vision
- Segment Anything Model: Foundation Model for Image Segmentation
Understanding Meta AI Latest Universal Segmentation Model.
Computer Vision
- Stable Diffusion: Basic Intuition Behind Generative AI
This article provides a general overview of Stable Diffusion and focuses on building a basic understanding of how generative artificial intelligence works.
Computer Vision
- DINOv2: Self-Supervised Computer Vision Models by Meta AI
Unleashing the Potential of Computer Vision with DINOv2: A Groundbreaking Self-Supervised Model by Meta AI.
Computer Vision
- How I Did Automatic Image Labeling Using Grounding DINO
I'm thrilled to share that recent advancements in the computer vision field, such as the emergence of groundbreaking zero-shot object detectors like Grounding DINO, have revolutionized the image labeling process.
Computer Vision
- Making Intelligent Document Processing Smarter: Part 1
This article attempts to measure the effect of various noises present in scanned documents on the performance of various APIs in the OCR segment.
Computer Vision
- 5 Reasons Why You Need Synthetic Data
Collecting and labeling data in the real world can be time-consuming and expensive. This data can also come with quality, diversity, and quantity issues. Fortunately, problems like these can be helped with synthetic data.
Computer Vision
- A Guide to Train an Image Classification Model Using Tensorflow
Classify images at scale and with very high accuracy with the advent of machine learning and deep learning algorithms.
Computer Vision
- YOLOv5 PyTorch Tutorial
Learn and train object detection model using YOLOv5.
Computer Vision
- 8 Best Python Image Manipulation Tools
Want to extract underlying data from images? This article lists some of the best Python image manipulation tools that help you transform images.
Computer Vision
- Multimodal Grounded Learning with Vision and Language
How to enable AI models to have similar capabilities: to communicate, to ground, and to learn from language.
Computer Vision
- How to Perform Motion Detection Using Python👁 KDnuggets Top Blog
In this article, we will specifically take a look at motion detection using a webcam of a laptop or computer and will create a code script to work on our computer and see its real-time example.
Computer Vision
- How to Convert an RGB Image to Grayscale
This post is about working with a mixture of color and grayscale images and needing to transform them into a uniform format - all grayscale. We'll be working in Python using the Pillow, Numpy, and Matplotlib packages.
Computer Vision
- Bounding Box Deep Learning: The Future of Video Annotation
Bounding box deep learning has several benefits that make it well-suited for video annotation.
Computer Vision
- 6 Things You Need To Know About Data Management And Why It Matters For Computer Vision
This article will explore a few areas that we feel are essential when assessing data management solutions for computer vision.
Computer Vision
- 5 Applications of Computer Vision
CV has the potential to transform industries and how they operate. Here are some of the most notable applications worth exploring.
Computer Vision
- Building a Visual Search Engine – Part 2: The Search Engine
Ever wonder how Google or Bing finds similar images to your image? The algorithms for generating text based 10 blue-links are very different from finding visually similar or related images. In this article, we will explain one such method to build a visual search engine. We will use the Caltech 101 dataset which contains images of common objects used in daily life.
Computer Vision
- Building a Visual Search Engine – Part 1: Data Exploration👁 KDnuggets Top Blog
Ever wonder how Google or Bing finds similar images to your image? The algorithms for generating text based 10 blue-links are very different from finding visually similar or related images. In this article, we will explain one such method to build a visual search engine. We will use the Caltech 101 dataset which contains images of common objects used in daily life.
Computer Vision
- TensorFlow for Computer Vision – Transfer Learning Made Easy
In this article, see how you can get above 90% accuracy on the validation set with a pretty straightforward approach. You'll also see what happens to the validation accuracy if we scale down the amount of training data by a factor of 20. Spoiler alert - it will remain unchanged.
Computer Vision
- Misconceptions About Semantic Segmentation Annotation
Semantic segmentation is a computer vision problem that entails putting related elements of an image into the same class. Read on to discover more, including the difficulties associated with annotation.
Computer Vision
- 👁 Silver Blog
Where NLP is heading
Natural language processing research and applications are moving forward rapidly. Several trends have emerged on this progress, and point to a future of more exciting possibilities and interesting opportunities in the field.
AI, Computer Vision, NLP, Transformer, Trends
- 10 AI Project Ideas in Computer Vision
The field of computer vision has seen the development of very powerful applications leveraging machine learning. These projects will introduce you to these techniques and guide you to more advanced practice to gain a deeper appreciation for the sophistication now available.
AI, Computer Vision, Project
- 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
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
- Real Time Image Segmentation Using 5 Lines of Code
PixelLib Library is a library created to allow easy integration of object segmentation in images and videos using few lines of python code. PixelLib now provides support for PyTorch backend to perform faster, more accurate segmentation and extraction of objects in images and videos using PointRend segmentation architecture.
Computer Vision, Image Processing, Machine Learning, Python, Segmentation
- How our Obsession with Algorithms Broke Computer Vision: And how Synthetic Computer Vision can fix it
Deep Learning radically improved Machine Learning as a whole. The Data-Centric revolution is about to do the same. In this post, we’ll take a look at the pitfalls of mainstream Computer Vision (CV) and discuss why Synthetic Computer Vision (SCV) is the future.
Algorithms, Computer Vision, Synthetic Data
- Computer Vision in Agriculture
Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.
Agriculture, AI, Computer Vision
- 3 Data Acquisition, Annotation, and Augmentation Tools
Check out these 3 projects found around GitHub that can help with your data acquisition, annotation, and augmentation tasks.
Computer Vision, Data Annotation, Data Labeling, Datasets, GitHub, NLP, Synthetic Data
- 👁 Silver Blog
Open Source Datasets for Computer Vision
Access to high-quality, noise-free, large-scale datasets is crucial for training complex deep neural network models for computer vision applications. Many open-source datasets are developed for use in image classification, pose estimation, image captioning, autonomous driving, and object segmentation. These datasets must be paired with the appropriate hardware and benchmarking strategies to optimize performance.
Computer Vision, Datasets, Open Source
- Machine Learning Skills – Update Yours This Summer
The process of mastering new knowledge often requires multiple passes to ensure the information is deeply understood. If you already began your journey into machine learning and data science, then you are likely ready for a refresher on topics you previously covered. This eight-week self-learning path will help you recapture the foundations and prepare you for future success in applying these skills.
Computer Vision, Data Science Skills, Deep Learning, Machine Learning, Skills
- Major changes: Where Analytics, Data Science, Machine Learning were applied in 2020/21
Our latest poll shows major change in where AI, Data Science, Machine Learning are being applied, with decline in interest in traditional fields like CRM/Consumer Analytics, and growth in applications to Computer Vision, COVID, Agriculture, and Education.
Agriculture, Computer Vision, Consumer Analytics, Education, Finance, Industry, Poll
- The Essential Guide to Transformers, the Key to Modern SOTA AI
You likely know Transformers from their recent spate of success stories in natural language processing, computer vision, and other areas of artificial intelligence, but are familiar with all of the X-formers? More importantly, do you know the differences, and why you might use one over another?
AI, Computer Vision, Deep Learning, NLP, Transformer
- 6 Mistakes To Avoid While Training Your Machine Learning Model
While training the AI model, multi-stage activities are performed to utilize the training data in the best manner, so that outcomes are satisfying. So, here are the 6 common mistakes you need to understand to make sure your AI model is successful.
Computer Vision, Data Labeling, Machine Learning, Mistakes
- A Beginner’s Guide to the CLIP Model
CLIP is a bridge between computer vision and natural language processing. I'm here to break CLIP down for you in an accessible and fun read! In this post, I'll cover what CLIP is, how CLIP works, and why CLIP is cool.
CLIP, Computer Vision, Machine Learning, NLP
- Evaluating Object Detection Models Using Mean Average Precision
In this article we will see see how precision and recall are used to calculate the Mean Average Precision (mAP).
Computer Vision, Metrics, Modeling, Object Detection
- Deep Learning-based Real-time Video Processing
In this article, we explore how to build a pipeline and process real-time video with Deep Learning to apply this approach to business use cases overviewed in our research.
Computer Vision, Deep Learning, Neural Networks, Video recognition
- OpenAI Releases Two Transformer Models that Magically Link Language and Computer Vision
OpenAI has released two new transformer architectures that combine image and language tasks in an fun and almost magical way. Read more about them here.
Computer Vision, NLP, OpenAI, Transformer
- 👁 Silver Blog
Top 10 Computer Vision Papers 2020
The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference.
AI, Computer Vision, Research
- Change the Background of Any Video with 5 Lines of Code
Learn to blur, color, grayscale and create a virtual background for a video with PixelLib.
Computer Vision, Image Processing, Machine Learning, Python, Segmentation, Video
- Computer Vision at Scale With Dask And PyTorch
A tutorial on conducting image classification inference using the Resnet50 deep learning model at scale with using GPU clusters on Saturn Cloud. The results were: 40x faster computer vision that made a 3+ hour PyTorch model run in just 5 minutes.
Computer Vision, Dask, Python, PyTorch, Scalability
- Adversarial Examples in Deep Learning – A Primer
Bigger compute has led to increasingly impressive deep learning computer vision model SOTA results. However most of these SOTA deep learning models are brought down to their knees when making predictions on adversarial images. Read on to find out more.
Adversarial, Computer Vision, Deep Learning
- 👁 Gold Blog
Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision
This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.
Computer Vision, Data Science, Deep Learning, Machine Learning, Neural Networks, NLP, Python
- 👁 Gold Blog
How to Acquire the Most Wanted Data Science Skills
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
- Change the Background of Any Image with 5 Lines of Code
Blur, color, grayscale and change the background of any image with a picture using PixelLib.
Computer Vision, Image Processing, Machine Learning, Python, Segmentation
- KDnuggets™ News 20:n41, Oct 28: Difference Between Junior and Senior Data Scientists; Ain’t No Such a Thing as a Citizen Data Scientist
The unspoken difference between junior and senior data scientists; Ain't No Such a Thing as a Citizen Data Scientist; How to become a Data Scientist: a step-by-step guide; Good-bye Big Data. Hello, Massive Data!; DeepMind Relies on this Old Statistical Method to Build Fair Machine Learning Models
Big Data, Career Advice, Citizen Data Scientist, Computer Vision, Data Science, Data Scientist, DeepMind, Statistical Modeling
- Roadmap to Computer Vision
Read this introduction to the main steps which compose a computer vision system, starting from how images are pre-processed, features extracted and predictions are made.
Computer Vision, Convolutional Neural Networks, Data Preprocessing, Neural Networks, Roadmap
- Deep Learning for Virtual Try On Clothes – Challenges and Opportunities
Learn about the experiments by MobiDev for transferring 2D clothing items onto the image of a person. As part of their efforts to bring AR and AI technologies into virtual fitting room development, they review the deep learning algorithms and architecture under development and the current state of results.
Computer Vision, Deep Learning, Fashion, Generative Adversarial Network, Generative Models, Humans, Image Generation
- A Guide to Preparing OpenCV for Android
This tutorial guides Android developers in preparing the popular library OpenCV for use. Using a step-by-step guide, the library will be imported into Android Studio and then can be used for performing any of the operations it supports, such as object detection, segmentation, tracking, and more.
Android, Computer Vision, Java, OpenCV
- Computer Vision Recipes: Best Practices and Examples
This is an overview of a great computer vision resource from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios.
Best Practices, Computer Vision, Microsoft, Python
- Accelerated Computer Vision: A Free Course From Amazon
Amazon's Machine Learning University is making its online courses available to the public, and this time we look at its Accelerated Computer Vision offering.
Amazon, Computer Vision, Courses, Free
- 3D Human Pose Estimation Experiments and Analysis
In this article, we explore how 3D human pose estimation works based on our research and experiments, which were part of the analysis of applying human pose estimation in AI fitness coach applications.
Analysis, Computer Vision, Humans, Sports, Video recognition
- Metrics to Use to Evaluate Deep Learning Object Detectors
It's important to understand which metric should be used to evaluate trained object detectors and which one is more important. Is mAP alone enough to evaluate the objector models? Can the same metric be used to evaluate object detectors on validation set and test set?
Computer Vision, Deep Learning, Metrics, Object Detection
- Scaling Computer Vision Models with Dataflow
Scaling Machine Learning models is hard and expensive. We will shortly introduce the Google Cloud service Dataflow, and how it can be used to run predictions on millions of images in a serverless way.
Computer Vision, Dataflow, Google, Python, Scalability
- Auto Rotate Images Using Deep Learning
Follow these 5 simple steps to auto rotate images and get the right angle in human photos using computer vision.
Computer Vision, Deep Learning, Face Detection, Image Processing
- KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills
A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset
Agriculture, Computer Vision, Courses, Data Science, Machine Learning, Mathematics, PyTorch, Tom Fawcett
- Bias in AI: A Primer
Those interested in studying AI bias, but who lack a starting point, would do well to check out this introductory set of slides and the accompanying talk on the subject from Google researcher Margaret Mitchell.
AI, Bias, Computer Vision, NLP
- 6 Easy Steps to Implement a Computer Vision Application Using Tensorflow.js
In this article, we are going to see how we can implement computer vision applications using tensorflow.js models.
Computer Vision, Javascript, TensorFlow
- Crop Disease Detection Using Machine Learning and Computer Vision
Computer vision has tremendous promise for improving crop monitoring at scale. We present our learnings from building such models for detecting stem and wheat rust in crops.
Agriculture, Computer Vision, Deep Learning, fast.ai
- Fighting Coronavirus With AI: Improving Testing with Deep Learning and Computer Vision
This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.
AI, Computer Vision, Coronavirus, COVID-19, Deep Learning, Healthcare
- Using AI to Identify Wildlife in Camera Trap Images from the Serengeti
With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.
Africa, AI, Computer Vision, Machine Learning
- Create Your Own Computer Vision Sandbox
This post covers a wide array of computer vision tasks, from automated data collection to CNN model building.
Computer Vision, Convolutional Neural Networks, Python
- The Future of Machine Learning
This summary overviews the keynote at TensorFlow World by Jeff Dean, Head of AI at Google, that considered the advancements of computer vision and language models and predicted the direction machine learning model building should follow for the future.
2020 Predictions, Computer Vision, Machine Learning, NLP, Transformer
- How to Convert a Picture to Numbers
Reducing images to numbers makes them amenable to computation. Let's take a look at the why and the how using Python and Numpy.
Computer Vision, Image Processing, numpy, Python
- 👁 Gold Blog
10 Free Top Notch Machine Learning Courses
Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
Books, Computer Vision, Courses, Deep Learning, Explainability, Graph Analytics, Interpretability, Machine Learning, NLP, Python
- Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models
The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.
Automated Machine Learning, Computer Vision, Google, Mobile, Open Source
- Research Guide for Video Frame Interpolation with Deep Learning
In this research guide, we’ll look at deep learning papers aimed at synthesizing video frames within an existing video.
Computer Vision, Deep Learning, Neural Networks, Video recognition
- A 2019 Guide to Human Pose Estimation
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
- Introduction to Image Segmentation with K-Means clustering
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
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
- Computer Vision for Beginners: Part 1
Image processing is performing some operations on images to get an intended manipulation. Think about what we do when we start a new data analysis. We do some data preprocessing and feature engineering. It’s the same with image processing.
Computer Vision, Deep Learning, Image Processing, Python
- An Overview of Human Pose Estimation with Deep Learning
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
- 👁 Silver Blog
NLP and Computer Vision Integrated
Computer vision and NLP developed as separate fields, and researchers are now combining these tasks to solve long-standing problems across multiple disciplines.
Computer Vision, NLP, Sciforce
- Building a Computer Vision Model: Approaches and datasets
How can we build a computer vision model using CNNs? What are existing datasets? And what are approaches to train the model? This article provides an answer to these essential questions when trying to understand the most important concepts of computer vision.
AI, Computer Vision, Deep Learning, ImageNet, Machine Learning, Neural Networks
- Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision
Dr. Takeo Kanade shared his life lessons from an illustrious 50-year career in Computer Vision at last year's Embedded Vision Summit. You have a chance to attend the 2019 Embedded Vision Summit, from May 20-23, in the Santa Clara Convention Center, Santa Clara CA.
AI, Algorithms, Computer Vision, Deep Learning, Machine Learning
- 👁 Silver Blog
Predict Age and Gender Using Convolutional Neural Network and OpenCV
Age and gender estimation from a single face image are important tasks in intelligent applications. As such, let's build a simple age and gender detection model in this detailed article.
Computer Vision, Convolutional Neural Networks, OpenCV, Python
- Pedestrian Detection in Aerial Images Using RetinaNet
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
- Object Detection with Luminoth
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
- Comparing MobileNet Models in TensorFlow
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
- How to do Everything in Computer Vision
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
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.
Pages: 1 2
Computer Vision, Image Recognition, NLP, Search, Search Engine, Word Embeddings
- Solve any Image Classification Problem Quickly and Easily
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
- Latest Trends in Computer Vision Technology and Applications
We investigate the advancements in deep learning, the rise of edge computing, object recognition with point cloud, VR and AR enhanced merged reality, semantic instance segmentation and more.
Applications, Computer Vision, InData Labs, Trends
- Building Surveillance System Using USB Camera and Wireless-Connected Raspberry Pi
Read this post to learn how to build a surveillance system using a USB camera plugged into Raspberry Pi (RPi) which is connected a PC using its wireless interface.
Pages: 1 2
Computer Vision, Python, Raspberry Pi, Security, Video recognition
- Basic Image Data Analysis Using Python – Part 4
Accessing the internal component of digital images using Python packages helps the user understand its properties, as well as its nature.
Computer Vision, Image Processing, Python
- Basic Image Data Analysis Using Python – Part 3
Accessing the internal component of digital images using Python packages becomes more convenient to help understand its properties, as well as nature.
Computer Vision, Image Processing, numpy, Python
- Introducing VisualData: A Search Engine for Computer Vision Datasets
Instead of building your own dataset, there already exists a rich collection of computer vision datasets contributed by academic researchers, hobbyists and companies.
Computer Vision, Datasets
- Basic Image Processing in Python, Part 2
We explain how to easily access and manipulate the internal components of digital images using Python and give examples from satellite image processing.
Computer Vision, Image Processing, numpy, Python
- Basic Image Data Analysis Using Numpy and OpenCV – Part 1
Accessing the internal component of digital images using Python packages becomes more convenient to understand its properties as well as nature.
Computer Vision, Image Processing, numpy, OpenCV, Python
- 👁 Silver Blog
DIY Deep Learning Projects
Inspired by the great work of Akshay Bahadur in this article you will see some projects applying Computer Vision and Deep Learning, with implementations and details so you can reproduce them on your computer.
Computer Vision, Data Science, Deep Learning, LinkedIn, Neural Networks, OpenCV, Python
- 👁 Gold Blog
How to Implement a YOLO (v3) Object Detector from Scratch in PyTorch: Part 1
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
- Road Lane Line Detection using Computer Vision models
A tutorial on how to implement a computer vision data pipeline for road lane detection used by self-driving cars.
Pages: 1 2
AI, Computer Vision, Data Science, Machine Learning, Python, Self-Driving Car
- 👁 Silver Blog, May 2017
Top 10 Machine Learning Videos on YouTube, updated
The top machine learning videos on YouTube include lecture series from Stanford and Caltech, Google Tech Talks on deep learning, using machine learning to play Mario and Hearthstone, and detecting NHL goals from live streams.
Andrew Ng, Computer Vision, Deep Learning, Geoff Hinton, Google, Machine Learning, Neural Networks, Robots, Video Games, Yaser Abu-Mostafa, Youtube
- Introduction to Trainspotting: Computer Vision, Caltrain, and Predictive Analytics
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
- 7 Steps to Understanding Computer Vision
A starting point for Computer Vision and how to get going deeper. Dive into this post for some overview of the right resources and a little bit of advice.
7 Steps, Computer Vision, Deep Learning, Neural Networks, Python
- 5 More Machine Learning Projects You Can No Longer Overlook
There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects.
Computer Vision, Data Preparation, Data Preprocessing, Javascript, Machine Learning, Natural Language Processing, NLP, Overlook, Python
- Microsoft is Becoming M(ai)crosoft
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.
AI, Artificial Intelligence, Computer Vision, Cortana, Machine Learning, Microsoft, Natural Language Processing, Speech Recognition
- Top 10 Machine Learning Videos on YouTube
The top machine learning videos on YouTube include lecture series from Stanford and Caltech, Google Tech Talks on deep learning, using machine learning to play Mario and Hearthstone, and detecting NHL goals from live streams.
Andrew Ng, Computer Vision, Deep Learning, Geoff Hinton, Google, Grant Marshall, Machine Learning, Neural Networks, Robots, Video Games, Youtube
