• Build Chinese version of machine learning project using TensorFlow
  • Chapter 1 explores and transforms data
    • TensorFlow’s primary data structure — tensors
    • Handling computational workflows — Data flow diagrams for TensorFlow
    • Run our program, session
    • Fundamental tensor methods
    • conclusion
  • Chapter 2 clustering
    • Learn from data — unsupervised learning
    • clustering
    • k-means
    • K nearest neighbor
    • Project 1 – K-means clustering on synthetic datasets
    • Item 2 – Nearest neighbor on a comprehensive data set
    • conclusion
  • Chapter 3 linear regression
    • Univariate linear modeling function
    • Determination of cost function
    • Minimizing cost function
    • The sample parts
    • Example 1 — Univariate linear regression
    • Example 2 — Multiple linear regression
    • conclusion
  • Chapter 4 Logistic regression
    • Problem description
    • The sigmoid function’s predecessor, the Logit function
    • The sigmoid function
    • Example 1 — Univariate logistic regression
    • Example 2 — Univariate logistic regression using SKflow
    • conclusion
  • Chapter 5 simple feedforward neural network
    • Preliminary concept
    • The first project – nonlinear synthetic function regression
    • The second project – using nonlinear regression to model vehicle fuel efficiency
    • Third project – Learning wine classification: multi-category classification
    • conclusion
  • Chapter 6 convolutional neural network
    • The origin of convolutional neural networks
    • Example 1 — MNIST numeric classification
    • Example 2 — Image classification using the CIFAR10 dataset
    • conclusion
  • Chapter 7 recurrent neural networks and LSTM
    • Recurrent neural network
    • Example 1 — Univariate time series prediction of energy consumption data
    • Example 2 — Write the music “A la” Bach
    • conclusion
  • Chapter 8 deep neural network
    • Deep neural network definition
    • Deep network architecture across time and space
    • Alexnet
    • Inception v3
    • Residual network (ResNet)
    • Example – Painting with Styles – VGG Style migration
    • conclusion
  • Chapter 9 Large-scale operation Model — Gpus and Services
    • GPU support on TensorFlow
    • Example 1 — Assign operations to the GPU
    • Example 2 — Compute Pi in parallel
    • Distributed TensorFlow
    • Example 3 — Distributed Pi computation
    • Example 4 — Run the distributed model in a cluster
    • conclusion
  • Chapter 10 Library Installation and other tips
    • Linux installation
    • Windows installation
    • MacOS X installation
    • conclusion