Topics To learn

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Papers published at the Neural Information Processing Systems Conference. (NIPS)


Design and Analysis of Algorithms MIT(X)

Great introduce to algorithm design. (Best to learn in parallel with SICP)

Algorithmic Aspects of Machine Learning MIT(X)

Nonnegative matrix factorization, tensor decomposition, sparse coding, learning mixture models, matrix completion and inference in graphical models. et.c

Introduction to Mathematical Programming MIT(X)


Scientific efficient computation (Bremen course)


  1. Nervana Graph (Intel nGraph) DOC
  2. NGraph Github
  3. Nervana home page
  5. NervanaSystems Neon Github


TensorRT developer Guide

Nvidia lib for improve computations.



Nvidia Teaching Kits

Software optimization resources

Best optimizing manuals resource
Performance Engineering of Software Systems MIT(X) Course


CE459: Programming for Performance, version 3 (Caltech)

ComputerVision NanoDegree 1000

In this program, you’ll learn the underlying math and programming concepts that drive pattern recognition, object and image classification tasks, and object tracking systems. This course will cover the latest in deep learning architectures used in industry, and you’ll combine current computer vision and deep learning techniques to power a variety of applications. With the practical skills you gain in this course, you’ll be able to program your own applications, extract information from any kind of image and spatial data, and solve real-world challenges.

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DeepLearning NanoDegree 600


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ComputerVision Robotics MicroMasters

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Computer Vision / CG Python (OLD)

CV Лекции и материалы - Общее:

  1. "Введение в компьютерное зрение и глубокое обучение" ВМК МГУ весна 2017
  2. "Введение в компьютерное зрение и глубокое обучение" ВМК МГУ 2008
  3. Курсы лаборатории компьютерной графики при ВМК МГУ


  1. GStreamer features
  2. Live stream with GStreamer примеры для gst-launch
  3. Howto
  4. GStreamer, RTP and live streaming, примеры для python
  5. Коллекции платных кодеков
  6. Hello World GStreamer на языке С


  1. Fast Event-based Corner Detection

CPython internals: A ten-hour codewalk through the Python interpreter source code

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Functional Programming on python with stepik

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Khan Academy courses

  1. Precalculus
  2. Multivariable Calculus


  1. Backprop2
  2. Backprop video
  3. Gradient Descent improving

Pro Tips about Human Face Detection

Here are some documents that provide information on Haar cascades.

More about hyperparameters, these are some great resources:

More specialized sources: