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C. Cui's Blog

Plan: Introduce the Softwares for Machine Learning

tensors_flowing
Tensorflow from Google

Software List: 

  1. Matlab Basic
  2. Matlab  Advanced:
    • LMS 
    • Softmax
    • SVM
    • Neural Network
    • Fizzy System
    • ANFIS.
  3. Python Basic
  4. Python Advanced:  
    • Numpy 
    • Pandas Pandas 
    • Matplotlib  
    • Scikit-learn  
    • Theano 
    • Tensorflow 
    • Keras 
  5. Torch Basic
  6. Torch for Deep Learning.

matlabpythonnumpypandasmatplotlibscikittheanotensorflowkerastorch

To be continued…

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  • Home
  • Machine Intelligence
    • Machine Learning
      • MathWorks: Introducing Machine Learning
      • Learning from data and Three learning principles
    • Open Courses, Free Softwares and Frameworks of Deep Learning
    • Neural Network and Deep Learning
      • Deep Learning Tutorial
      • Private: Sparse Autoencoder
      • Private: Restricted Boltzmann Machines
      • Private: Convolutional Neural Networks
    • Reading Notebook
      • Fast Neural Style Transfer by PyTorch (Mac OS)
      • Image Style Transfer Using ConvNets by TensorFlow (Windows)
      • Note about Markov Chain Monte Carlo (MCMC) and Restricted Boltzmann Machine (RBM)
      • What soft skills do software developer need?
      • Should you ask a Question during Seminar?
      • How to start a science paper from a beginner
      • Writing in Chinese
        • 你是谁，从哪儿来，到哪儿去
        • 脑子中的想法，请你一定要写出来
  • Tutorial
    • Sharing My Data Science Notebook (Python & TensorFlow) on GitHub
    • Plan: Introduce the Softwares for Machine Learning
    • Learning from data and Three learning principles
    • Deep Learning – SIMPLIFIED (27 vedios)
    • Building ConvNets on MNIST dataset by TensorFlow with the new WIN10 GPU Monitor
    • A Taste of TensorFlow on My Android Phone (II)
    • A Taste of TensorFlow on My Android Phone
    • Neural Networks for Machine Learning — Geoffrey Hinton
    • Fast Neural Style Transfer by PyTorch (Mac OS)
    • Stanford CS229 Machine Learning
    • Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition
    • Machine Learning in Chinese by Morvan Zhou
      • 莫烦 Python 教学 — 机器学习 Machine Learning
      • 莫烦 Python 教学 — 神经网络 Deep Learning
  • Contact
    • About Me
    • Research and Publication
Follow C. Cui's Blog on WordPress.com
  • Home
  • Machine Intelligence
    • Machine Learning
      • MathWorks: Introducing Machine Learning
      • Learning from data and Three learning principles
    • Open Courses, Free Softwares and Frameworks of Deep Learning
    • Neural Network and Deep Learning
      • Deep Learning Tutorial
      • Private: Sparse Autoencoder
      • Private: Restricted Boltzmann Machines
      • Private: Convolutional Neural Networks
    • Reading Notebook
      • Fast Neural Style Transfer by PyTorch (Mac OS)
      • Image Style Transfer Using ConvNets by TensorFlow (Windows)
      • Note about Markov Chain Monte Carlo (MCMC) and Restricted Boltzmann Machine (RBM)
      • What soft skills do software developer need?
      • Should you ask a Question during Seminar?
      • How to start a science paper from a beginner
      • Writing in Chinese
        • 你是谁，从哪儿来，到哪儿去
        • 脑子中的想法，请你一定要写出来
  • Tutorial
    • Sharing My Data Science Notebook (Python & TensorFlow) on GitHub
    • Plan: Introduce the Softwares for Machine Learning
    • Learning from data and Three learning principles
    • Deep Learning – SIMPLIFIED (27 vedios)
    • Building ConvNets on MNIST dataset by TensorFlow with the new WIN10 GPU Monitor
    • A Taste of TensorFlow on My Android Phone (II)
    • A Taste of TensorFlow on My Android Phone
    • Neural Networks for Machine Learning — Geoffrey Hinton
    • Fast Neural Style Transfer by PyTorch (Mac OS)
    • Stanford CS229 Machine Learning
    • Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition
    • Machine Learning in Chinese by Morvan Zhou
      • 莫烦 Python 教学 — 机器学习 Machine Learning
      • 莫烦 Python 教学 — 神经网络 Deep Learning
  • Contact
    • About Me
    • Research and Publication
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