constant e

Derivative

gradient

Taylor

gini coefficient

Information entropy and combination number

gradient descent

Newton's method

Linear spaces and linear transformations

Basic concepts of matrices

state transition matrix

Feature vector

Correlated multiplication of matrices

QR decomposition of matrix

Symmetric matrix, orthogonal matrix, positive definite matrix

SVD decomposition of matrices

Derivatives of matrices

Matrix mapping/projection

Calculus and Approximation Theory

Basic concepts of limit, differential and integral

Use the idea of ​​approximation to understand differential calculus, and use integral methods to understand probability.

Basics of Probability Theory

classical model

Common probability distributions

Theorem of large numbers and central limit theorem

Covariance (matrix) and correlation coefficient

Maximum likelihood estimation and maximum a posteriori estimation

Basic concepts of convex optimization

Convex set

convex function

Standard form of convex optimization problem

Lagerange dualization of convex optimization

Quick Start with Python

Scientific computing library Numpy

Data analysis and processing library Numpy

Visualization library Matplotlib

Easier visualization with Seaborn

Algorithm explanation

Project walkthrough

Computer Vision-Convolutional Neural Network

Third generation object detection framework

Basic principles of convolutional neural networks

Detailed explanation of convolution parameters

Case practice CNN network

Network model training skills

Classic network architecture and object detection tasks

Basic operations of deep learning framework Tensorflow

Tensorflow framework constructs regression model

Tensorflow neural network model

Tensorflow builds CNN network

Tensorflow builds RNN network

Tensorflow loads the trained model

Deep learning project practice-verification code recognition

Deep learning framework Caffe network configuration

Caffe production data source

Caffe framework tips

Common tools of Caffe framework

Project walkthrough: Face detection data source production and network training (based on Caffe)

Project walkthrough: Implementing face detection (based on Caffe)

Project walkthrough: first stage network training for key point detection (based on Caffe)

Project walkthrough: second stage model training for key point detection (based on Caffe)

Project Walkthrough: Adversarial Generative Network (based on Tensorflow)

Project walkthrough: LSTM sentiment analysis (based on Tensorflow)

Project walkthrough: Robot writes Tang poetry (based on Tensorflow)

Project walkthrough: text classification task interpretation and environment configuration

Project walkthrough: text classification practice (based on Tensorflow)

Project walkthrough: Reinforcement learning basics (based on Tensorflow)

Project walkthrough: DQN lets AI play games by itself (based on Tensorflow)