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gitbook_docs
  • Introduction
  • Machine Learning
    • Recommended Courses
      • For Undergrad Research
      • Math for Machine Learning
    • ML Notes
      • Covariance Correlation
      • Feature Selection
      • Linear Regression
      • Entropy, Cross-Entropy, KL Divergence
      • Bayesian Classifier
        • Terminology Review
        • Bayesian Classifier for Normally Distributed classes
      • Linear Discriminant Analysis
      • Logistic Regression
        • Logistic Regression Math
      • Logistic Regression-MaximumLikelihood
      • SVM
        • SVM concept
        • SVM math
      • Cross Validation
      • Parameter, Density Estimation
        • MAP, MLE
        • Gaussian Mixture Model
      • E-M
      • Density Estimation(non-parametric)
      • Unsupervised Learning
      • Clustering
      • kNN
      • WaveletTransform
      • Decision Tree
    • Probability and Statistics for Machine Learning
      • Introduction
      • Basics of Data Analysis
      • Probability for Discrete Random Variable
      • Poisson Distribution
      • Chi-Square Distribution
      • P-value and Statistical Hypothesis
      • Power and Sample Size
      • Hypothesis Test Old
      • Hypothesis Test
      • Multi Armed Bandit
      • Bayesian Inference
      • Bayesian Updating with Continuous Priors
      • Discrete Distribution
      • Comparison of Bayesian and frequentist inference
      • Confidence Intervals for Normal Data
      • Frequenist Methods
      • Null Hypothesis Significance Testing
      • Confidence Intervals: Three Views
      • Confidence Intervals for the Mean of Non-normal Data
      • Probabilistic Prediction
  • Industrial AI
    • PHM Dataset
    • BearingFault_Journal
      • Support Vector Machine based
      • Autoregressive(AR) model based
      • Envelope Extraction based
      • Wavelet Decomposition based
      • Prediction of RUL with Deep Convolution Nueral Network
      • Prediction of RUL with Information Entropy
      • Feature Model and Feature Selection
    • TempCore Journal
      • Machine learning of mechanical properties of steels
      • Online prediction of mechanical properties of hot rolled steel plate using machine learning
      • Prediction and Analysis of Tensile Properties of Austenitic Stainless Steel Using Artificial Neural
      • Tempcore, new process for the production of high quality reinforcing
      • TEMPCORE, the most convenient process to produce low cost high strength rebars from 8 to 75 mm
      • Experimental investigation and simulation of structure and tensile properties of Tempcore treated re
    • Notes
  • LiDAR
    • Processing of Point Cloud
    • Intro. 3D Object Detection
    • PointNet
    • PointNet++
    • Frustrum-PointNet
    • VoxelNet
    • Point RCNN
    • PointPillars
    • LaserNet
  • Simulator
    • Simulator List
    • CARLA
    • Airsim
      • Setup
      • Tutorial
        • T#1
        • T#2
        • T#3: Opencv CPP
        • T#4: Opencv Py
        • Untitled
        • T#5: End2End Driving
  • Resources
    • Useful Resources
    • Github
    • Jekyll
  • Reinforcement Learning
    • RL Overview
      • RL Bootcamp
      • MIT Deep RL
    • Textbook
    • Basics
    • Continuous Space RL
  • Unsupervised Learning
    • Introduction
  • Unclassified
    • Ethics
    • Conference Guideline
  • FPGA
    • Untitled
  • Numerical Method
    • NM API reference
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  • Wiki of Deep Learning / Machine Learning
  • Machine Learning
  • Deep Learning Framework
  • Programming DL
  • Simulator
  • Resources

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Introduction

Wiki of Deep Learning / Machine Learning

Machine Learning

Deep Learning for Perception

  • DL Courses

    • Recommended Courses

    • Resources

    • Tutorial

  • Deep Learning Papers

  • Deep Learning Case Study

    • Anomaly Detection in Time Series

    • Face Eye Lip Detection

Deep Learning Framework

  • TensorFlow

    • Install

    • Cheat Sheet

    • Tutorial

  • Keras

    • Cheat Sheet

    • Tutorial Keras

  • PyTorch

    • Install

    • Cheat Sheet

    • Tutorial

Programming DL

  • Python

    • Install

    • Cheat Sheet

    • Tips

  • OpenCV

    • MATLAB-OpenCV

  • DL Library

    • NumPy

      • Install

      • How to use

    • SciPy, scikit-learn

      • Install

      • How to use

    • MATPlot

      • Install

      • How to use

    • Pandas

      • Install

      • How to use

    • Anaconda

      • Install

      • How to use

    • Git_Github

      • Install

      • How to use

  • IDE

    • Google Codelab

      • Install

      • Setup

      • How to use

    • Visual Studio Code

      • Install

      • Setup

      • How to use

    • Jupyter Notebook

      • Install

      • How to use

Simulator

  • CARLA

  • Airsim

    • Setup

    • Tutorial

      • T#1

      • T#2

      • T#3: Opencv CPP

      • T#4: Opencv Py

      • Untitled

      • T#5: End2End Driving

Resources

  • Useful Resources

  • Github

NextRecommended Courses

Last updated 3 years ago

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