Table of Contents
- Mathematics for Robotics
- Computer Vision
- Machine Learning
- Planning
- Deep Learning
- Robot Operating System
Legend --
π₯ -- Video Tutorial/Lectureπ -- Reading Material/Blog Post
Mathematics for Robotics
- Homogeneous Co-ordinates
π₯ - The Truth behind Homogeneous Coordinates
- Linear Algebra Review by Andrew Ng
π - Probability Theory Review by Andrew Ng
π - Introduction to Machine Learning -- 10601, Carnegie Mellon University Maths Review --
- QR Factorization and Singular Value Decomposition
Computer Vision
Courses
- Introduction to Computer Vision course by Udacity and GaTech
π₯
Books
- Programming Computer Vision with Python by Jan Erik Solem
π -- FREE -- Python
Blogs
- Musings of a Computer Scientist -- Andrej Karpathy
π - PyImageSearch -- Adrian Rosebrock
π - Tombone's Computer Vision Blog -- Tomasz Malisiewicz
π - Machine Learning Mastery -- Jason Brownlee
π - Learn OpenCV -- Satya Mallick
π
Randomly choosen good material
- Slides on Harris Corner Detector
- Tutorial on Binary Descriptors
- Binary robust independent elementary features (βBRIEFβ) understanding
- Seperable Filter in MATLAB using
svd
- Computer Vision: What is the difference between HOG and SIFT feature descriptor?
- GIST descriptor Code
- 1D and 2D Gaussian Derivative Visualization
- How does the Kinect work?
- Notes on Camera Calibration, DLT, SVD
- Camera Caliberation
- Visual SLAM
- Visual SLAM Notes
- Visual Odometry
Datasets
Machine Learning
- Convex Optimization notes by Andrew Ng -- Part 1 Part 2
π - Maximum Likelihood Examples by Pieter Abbeel
π₯ - Laplace Smoothing by Pieter Abbeel
π₯ - Linear Discriminant Analysis 1
π - Linear Discriminant Analysis 2 and Locally Linear Embedding by Cyrill Stachniss
π₯ - Mahalanobis Distance
π₯ - Gaussian Processes for Dummies
π - A gentle introduction to Gradient Boosting
π - An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
π - [Cover's Theorem](Cover's theorem) -- [WIKI]
π - How does centering the data get rid of the intercept in regression and PCA?
- What is an intuitive explanation of the relation between PCA and SVD?
- Nice Readings on sampling
- l0-Norm, l1-Norm, l2-Norm, β¦ , l-infinity Norm
Optimization
Probabilistic Graphical Models (PGMs)
Planning
- A* Search by Pieter Abbeel
π₯ - Nice Video -- The piano mover's problem
- Robotics Motion Planning Slides
- Why is the A* search heuristic optimal even if it underestimates costs?
Graph Theory
Deep Learning
Deep Learning Courses
- Caltech's introductory deep learning course taught by Yasser Abu-Mostafa
π₯ - Stanford CS224d: Deep Learning for Natural Language Processing (video, slides, tutorials)
π - Stat212b: Topics Course on Deep Learning
- Machine Learning for Artists
Awesome Deep Nets Visualizations
- An Interactive Node-Link Visualization of Convolutional Neural Networks
- Tinker With a Neural Network Right Here in Your Browser
Robot Operating System
Books
- A Gentle Introduction to ROS by Jason M. O'Kane
π -- FREE C++ - Programming Robots with ROS Morgan Quigley et al.
π -- PAID Python