instillai/TensorFlow-Roadmap
Là một công cụ AI, instillai/TensorFlow-Roadmap đã đạt 87 sao trên GitHub, ngôn ngữ Python. :satellite: Organized & Useful Resources about Deep Learning with TensorFlow
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TensorFlow Roadmap
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################################################### Download Free TensorFlow Roadmap EBook ###################################################
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################# Table of Contents ################# .. contents:: :local: :depth: 3
============ Introduction
The purpose of this project is to introduce a shortcut to developers and researcher for finding useful resources about TensorFlow.
Motivation
There are different motivations for this open source project.
Why using TensorFlow?
A deep learning is of great interest these days, the crucial necessity for rapid and optimized implementation of the algorithms
and designing architectures is the software environment. TensorFlow is designed to facilitate this goal. The strong advantage of
TensorFlow is it flexibility is designing highly modular model which also can be a disadvantage too for beginners since lots of
the pieces must be considered together for creating the model. This issue has been facilitated as well by developing high-level APIs
such as Keras <https://keras.io/>_ and Slim <https://github.com/tensorflow/models/blob/master/inception/inception/slim/README.md//>_
which gather lots of the design puzzle pieces. The interesting point about TensorFlow is that its trace can be found anywhere these days.
Lots of the researchers and developers are using it and its community is growing with the speed of light! So the possible issues can
be overcame easily since they might be the issues of lots of other people considering a large number of people involved in TensorFlow community.
What's the point of this open source project?
There other similar repositories similar to this repository and are very
comprehensive and useful and to be honest they made me ponder if there is
a necessity for this repository! A great example is awesome-tensorflow <https://github.com/jtoy/awesome-tensorflow>_
repository which is a curated list of different TensorFlow resources.
The point of this repository is that the resources are being targeted. The organization of the resources is such that the user can easily find the things he/she is looking for. We divided the resources to a large number of categories that in the beginning one may have a headache!!! However, if someone knows what is being located, it is very easy to find the most related resources. Even if someone doesn't know what to look for, in the beginning, the general resources have been provided.
How to make the most of this effort
The written and visual resources have been split. Moreover, As one can search in the documentation, the number of categories might look to be too much. For finding the most relevant resources, please at first look through the general resources.
============================ Entrance to TensorFlow World
In this section, different TensorFlow topics and their associated resources will be addressed.
Installation
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First of all, the TensorFlow must be installed!
Installing TensorFlow_: Official TensorFLow installationInstall TensorFlow from the source_: A comprehensive guide on how to install TensorFlow from the source using python/anacondaTensorFlow Installation_: A short TensorFlow installation guide powered by NVIDIA7 SIMPLE STEPS TO INSTALL TENSORFLOW ON WINDOWS_: A concise tutorial for installing TensorFlow on Windows
.. _Installing TensorFlow: https://www.tensorflow.org/install/ .. _Install TensorFlow from the source: https://github.com/astorfi/TensorFlow-World/tree/master/docs/tutorials/installation .. _TensorFlow Installation: http://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-installation.html .. _7 SIMPLE STEPS TO INSTALL TENSORFLOW ON WINDOWS: http://saintlad.com/install-tensorflow-on-windows/
Install TensorFlow on Ubuntu_: A comprehensive tutorial on how to install TensorFlow on UbuntuInstallation of TensorFlow_: The video covers how to setup TensorFlowInstalling CPU and GPU TensorFlow on Windows_: A tutorial on TensorFlow installation for WindowsInstalling the GPU version of TensorFlow for making use of your CUDA GPU_: A GPU-targeted TensoFlow installation
.. _Install TensorFlow on Ubuntu: https://www.youtube.com/watch?v=_3JFEPk4qQY&t=3s .. _Installation of TensorFlow: https://www.youtube.com/watch?v=CvspEt8kSIg .. _Installing CPU and GPU TensorFlow on Windows: https://www.youtube.com/watch?v=r7-WPbx8VuY .. _Installing the GPU version of TensorFlow for making use of your CUDA GPU: https://www.youtube.com/watch?v=io6Ajf5XkaM
Getting Started
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This part points to resources on how to start to code with TensorFLow
Getting Started With TensorFlow Framework_: This guide gets you started programming in TensorFlowlearning TensorFlow Deep Learning_:A great resource to startWelcome to TensorFlow World_: A simple and concise start to TensorFLow
.. _learning TensorFlow Deep Learning: http://learningtensorflow.com/getting_started/ .. _Getting Started With TensorFlow Framework: https://www.tensorflow.org/get_started/get_started .. _Welcome to TensorFlow World: https://github.com/astorfi/TensorFlow-World/tree/master/docs/tutorials/0-welcome
Gentlest Introduction to Tensorflow <https://www.youtube.com/watch?v=dYhrCUFN0eM>_TensorFlow in 5 Minutes <https://www.youtube.com/watch?v=2FmcHiLCwTU/>_Deep Learning with TensorFlow - Introduction to TensorFlow <https://www.youtube.com/watch?v=MotG3XI2qSs>_TensorFlow Tutorial (Sherry Moore, Google Brain) <https://www.youtube.com/watch?v=Ejec3ID_h0w>_Deep Learning with Neural Networks and TensorFlow Introduction <https://www.youtube.com/watch?v=oYbVFhK_olY>_A fast with TensorFlow <https:/www.youtube.com/watch?v=Q-FF_0NAT3s>_
Going Deeper in TensorFLow
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Advanced machine learning users can go deeper in TensorFlow in order to hit the root. Scratching the surface may never take us too further!
TensorFlow Mechanics_: More experienced machine learning users can dig more in TensorFlowAdvanced TensorFlow_: Advanced Tutorials in TensorFlowWe Need to Go Deeper_: A Practical Guide to Tensorflow and InceptionWide and Deep Learning - Better Together with TensorFlow_: A tutorial by Google Research Blog
.. _TensorFlow Mechanics: https://www.tensorflow.org/get_started/mnist/mechanics .. _Advanced TensorFlow: https://github.com/sjchoi86/advanced-tensorflow .. _We Need to Go Deeper: https://medium.com/initialized-capital/we-need-to-go-deeper-a-practical-guide-to-tensorflow-and-inception-50e66281804f .. _Wide and Deep Learning - Better Together with TensorFlow: https://research.googleblog.com/2016/06/wide-deep-learning-better-together-with.html
TensorFlow DeepDive_: More experienced machine learning users can dig more in TensorFlowGo Deeper - Transfer Learning_: TensorFlow and Deep LearningDistributed TensorFlow - Design Patterns and Best Practices_: A talk that was given at the Advanced Spark and TensorFlow MeetupDistributed TensorFlow Guide_Fundamentals of TensorFlow_TensorFlow Wide and Deep - Advanced Classification the easy way_Tensorflow and deep learning - without a PhD_: A great tutorial on TensoFLow workflow
.. _TensorFlow DeepDive: https://www.youtube.com/watch?v=T0H6zF3K1mc .. _Go Deeper - Transfer Learning: https://www.youtube.com/watch?v=iu3MOQ-Z3b4 .. _Distributed TensorFlow - Design Patterns and Best Practices: https://www.youtube.com/watch?v=YAkdydqUE2c .. _Distributed TensorFlow Guide: https://github.com/tmulc18/Distributed-TensorFlow-Guide .. _Fundamentals of TensorFlow: https://www.youtube.com/watch?v=EM6SU8QVSlY .. _TensorFlow Wide and Deep - Advanced Classification the easy way: https://www.youtube.com/watch?v=WKgNNC0VLhM .. _Tensorflow and deep learning - without a PhD: https://www.youtube.com/watch?v=vq2nnJ4g6N0
============================ Programming with TensorFlow
The references here, deal with the details of programming and writing TensorFlow code.
Reading data and input pipeline
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The first part is always how to prepare data and how to provide the pipeline to feed it to TensorFlow. Usually providing the input pipeline can be complicated, even more than the structure design!
Dataset API for TensorFlow Input Pipelines_: A TensorFlow official documentation on Using the Dataset API for TensorFlow Input PipelinesTesnowFlow input pipeline_: Input pipeline provided by Stanford.TensorFlow input pipeline example_: A working example.TensorFlow Data Input_: TensorFlow Data Input: Placeholders, Protobufs & QueuesReading data_: The official documentation by the TensorFLow on how to read databasics of reading a CSV file_: A tutorial on reading a CSV fileCustom Data Readers_: Official documentation on this how to define a reader.
.. _Dataset API for TensorFlow Input Pipelines: https://github.com/tensorflow/tensorflow/tree/v1.2.0-rc1/tensorflow/contrib/data .. _TesnowFlow input pipeline: http://web.stanford.edu/class/cs20si/lectures/slides_09.pdf .. _TensorFlow input pipeline example: http://ischlag.github.io/2016/06/19/tensorflow-input-pipeline-example/ .. _TensorFlow Data Input: https://indico.io/blog/tensorflow-data-inputs-part1-placeholders-protobufs-queues/ .. _Reading data: https://www.tensorflow.org/programmers_guide/reading_data .. _basics of reading a CSV file: http://learningtensorflow.com/ReadingFilesBasic/ .. _Custom Data Readers: https://www.tensorflow.org/extend/new_data_formats
Tensorflow tutorial on TFRecords_: A tutorial on how to transform data into TFRecords
.. _Tensorflow tutorial on TFRecords: https://www.youtube.com/watch?v=F503abjanHA
An introduction to TensorFlow queuing and threading_: A tutorial on how to understand and create queues an efficient pipelines
.. _An introduction to TensorFlow queuing and threading: http://adventuresinmachinelearning.com/introduction-tensorflow-queuing/
Variables
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Variables are supposed to hold the parameters and supersede by new values as the parameters are updated. Variables must be clearly set and initialized.
Creation, Initialization
Variables Creation and Initialization_: An official documentation on setting up variablesIntroduction to TensorFlow Variables - Creation and Initialization_: This tutorial deals with defining and initializing TensorFlow variablesVariables_: An introduction to variables
.. _Variables Creation and Initialization: https://www.tensorflow.org/programmers_guide/variables .. _Introduction to TensorFlow Variables - Creation and Initialization: http://machinelearninguru.com/deep_learning/tensorflow/basics/variables/variables.html .. _Variables: http://learningtensorflow.com/lesson2/
Saving and restoring
Saving and Loading Variables_: The official documentation on saving and restoring variablessave and restore Tensorflow models_: A quick tutorial to save and restore Tensorflow models
.. _Saving and Loading Variables: https://www.tensorflow.org/programmers_guide/variables .. _save and restore Tensorflow models: http://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/
Sharing Variables
Sharing Variables_: The official documentation on how to share variables
.. _Sharing Variables: https://www.tensorflow.org/programmers_guide/variable_scope
Deep Learning with Tensorflow - Tensors and Variables_: A Tensorflow tutorial for introducing Tensors, Variables and PlaceholdersTensorflow Variables_: A quick introduction to TensorFlow variablesSave and Restore in TensorFlow_: TensorFlow Tutorial on Save and Restore variables
.. _Deep Learning with Tensorflow - Tensors and Variables: https://www.youtube.com/watch?v=zgV-WzLyrYE .. _Tensorflow Variables: https://www.youtube.com/watch?v=UYyqNH3r4lk .. _Save and Restore in TensorFlow: https://www.tensorflow.org/programmers_guide/variable_scope
TensorFlow Utilities
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Different utilities empower TensorFlow for faster computation in a more monitored manner.
Supervisor
Supervisor - Training Helper for Days-Long Trainings_: The official documentation for TensorFLow Supervisor.Using TensorFlow Supervisor with TensorBoard summary groups_: Using both TensorBoard and the Supervisor for profitTensorflow example_: A TensorFlow example using Supervisor.
.. _Supervisor - Training Helper for Days-Long Trainings: https://www.tensorflow.org/programmers_guide/supervisor .. _Using TensorFlow Supervisor with TensorBoard summary groups: https://dev.widemeadows.de/2017/01/21/using-tensorflows-supervisor-with-tensorboard-summary-groups/ .. _Tensorflow example: http://codata.colorado.edu/notebooks/tutorials/tensorflow_example_davis_yoshida/
TensorFlow Debugger
TensorFlow Debugger (tfdbg) Command-Line-Interface Tutorial_: Official documentation for using debugger for MNISTHow to Use TensorFlow Debugger with tf.contrib.learn_: A more high-level method to use the debugger.Debugging TensorFlow Codes_: A Practical Guide for Debugging TensorFlow CodesDebug TensorFlow Models with tfdbg_: A tutorial by Google Developers Blog
.. _TensorFlow Debugger (tfdbg) Command-Line-Interface Tutorial: https://www.tensorflow.org/programmers_guide/debugger .. _How to Use TensorFlow Debugger with tf.contrib.learn: https://www.tensorflow.org/programmers_guide/tfdbg-tflearn .. _Debugging TensorFlow Codes: https://github.com/wookayin/tensorflow-talk-debugging .. _Debug TensorFlow Models with tfdbg: https://developers.googleblog.com/2017/02/debug-tensorflow-models-with-tfdbg.html
MetaGraphs
Exporting and Importing a MetaGraph_: Official TensorFlow documentationModel checkpointing using meta-graphs in TensorFlow_: A working example
.. _Exporting and Importing a MetaGraph: https://www.tensorflow.org/programmers_guide/meta_graph .. _Model checkpointing using meta-graphs in TensorFlow: http://www.seaandsailor.com/tensorflow-checkpointing.html
Tensorboard
TensorBoard - Visualizing Learning_: Official documentation by TensorFlow.TensorFlow Ops_: Provided by StanfordVisualisation with TensorBoard_: A tutorial on how to create and visualize a graph using TensorBoardTensorboard_: A brief tutorial on Tensorboard
.. _TensorBoard - Visualizing Learning: https://www.tensorflow.org/get_started/summaries_and_tensorboard .. _TensorFlow Ops: http://web.stanford.edu/class/cs20si/lectures/notes_02.pdf .. _Visualisation with TensorBoard: http://learningtensorflow.com/Visualisation/ .. _Tensorboard: http://edwardlib.org/tutorials/tensorboard
Hands-on TensorBoard (TensorFlow Dev Summit 2017)_: An introduction to the amazing things you can do with TensorBoardTensorboard Explained in 5 Min_: Providing the code for a simple handwritten character classifier in Python and visualizing it in TensorboardHow to Use Tensorboard_: Going through a bunch of different features in Tensorboard
.. _Hands-on TensorBoard (TensorFlow Dev Summit 2017): https://www.youtube.com/watch?v=eBbEDRsCmv4 .. _Tensorboard Explained in 5 Min: https://www.youtube.com/watch?v=3bownM3L5zM .. _How to Use Tensorboard: https://www.youtube.com/watch?v=fBVEXKp4DIc
==================== TensorFlow Tutorials
This section is dedicated to provide tutorial resources on the implementation of different models with TensorFlow.
Linear and Logistic Regression
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TensorFlow Linear Model Tutorial_: Using TF.Learn API in TensorFlow to solve a binary classification problemLinear Regression in Tensorflow_: Predicting house prices in Boston areaLinear regression with Tensorflow_: Make use of tensorflow for numeric computation using data flow graphsLogistic Regression in Tensorflow with SMOTE_: Implementation of Logistic Regression in TensorFlowA TensorFlow Tutorial - Email Classification_: Using a simple logistic regression classifierLinear Regression using TensorFlow_: Training a linear model by TensorFlowLogistic Regression using TensorFlow_: Training a logistic regression by TensorFlow for binary classification
.. _TensorFlow Linear Model Tutorial: https://www.tensorflow.org/tutorials/wide .. _Linear Regression in Tensorflow: https://aqibsaeed.github.io/2016-07-07-TensorflowLR/ .. _Linear regression with Tensorflow: https://www.linkedin.com/pulse/linear-regression-tensorflow-iv%C3%A1n-corrales-solera .. _Logistic Regression in Tensorflow with SMOTE: https://aqibsaeed.github.io/2016-08-10-logistic-regression-tf/ .. _A TensorFlow Tutorial - Email Classification: http://jrmeyer.github.io/tutorial/2016/02/01/TensorFlow-Tutorial.html .. _Linear Regression using TensorFlow: https://github.com/astorfi/TensorFlow-World/tree/master/docs/tutorials/2-basics_in_machine_learning/linear_regression .. _Logistic Regression using TensorFlow: https://github.com/astorfi/TensorFlow-World/tree/master/docs/tutorials/2-basics_in_machine_learning/logistic_regression
Deep Learning with Tensorflow - Logistic Regression_: A tutorial on Logistic RegressionDeep Learning with Tensorflow - Linear Regression with TensorFlow_: A tutorial on Linear Regression
.. _Deep Learning with Tensorflow - Logistic Regression: https://www.youtube.com/watch?v=4cBRxZavvTo&t=1s .. _Deep Learning with Tensorflow - Linear Regression with TensorFlow: https://www.youtube.com/watch?v=zNalsMIB3NE
Convolutional Neural Networks
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Convolutional Neural Networks_: Official TensorFlow documentationConvolutional Neural Networks using TensorFlow_: Training a classifier using convolutional neural networksImage classifier using convolutional neural network_: Building a convolutional neural network based image classifierConvolutional Neural Network CNN with TensorFlow tutorial_: It covers how to write a basic convolutional neural network within TensorFlow with PythonDeep Learning CNNs in Tensorflow with GPUs_: Designing the architecture of a convolutional neural network (CNN)
.. _Convolutional Neural Networks: https://www.tensorflow.org/tutorials/deep_cnn .. _Convolutional Neural Networks using TensorFlow: https://github.com/astorfi/TensorFlow-World/tree/master/docs/tutorials/3-neural_network/convolutiona_neural_network .. _Image classifier using convolutional neural network: http://cv-tricks.com/tensorflow-tutorial/training-convolutional-neural-network-for-image-classification/ .. _Convolutional Neural Network CNN with TensorFlow tutorial: https://pythonprogramming.net/cnn-tensorflow-convolutional-nerual-network-machine-learning-tutorial/ .. _Deep Learning CNNs in Tensorflow with GPUs: https://hackernoon.com/deep-learning-cnns-in-tensorflow-with-gpus-cba6efe0acc2
Deep Learning with Neural Networks_: Convolutional Neural Networks with TensorFlowTensorFlow Tutorial_: Convolutional Neural NetworkUnderstanding Convolution with TensorFlow_: A tutorial on Convolution operation with TensorFlowCNN - Deep Learning with Tensorflow_: Convolutional Network with TensorFlow
.. _Deep Learning with Neural Networks: https://www.youtube.com/watch?v=mynJtLhhcXk .. _TensorFlow Tutorial: https://www.youtube.com/watch?v=HMcx-zY8JSg .. _Understanding Convolution with TensorFlow: https://www.youtube.com/watch?v=ETdaP_bBNWc .. _CNN - Deep Learning with Tensorflow: https://www.youtube.com/watch?v=yL-MkBSv18c
Recurrent Neural Networks
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Recurrent Neural Networks_: TensorFlow official documentationHow to build a Recurrent Neural Network in TensorFlow_: How to build a simple working Recurrent Neural Network in TensorFlowRecurrent Neural Networks in Tensorflow_: Building a vanilla recurrent neural network (RNN) from the ground up in TensorflowRNNs in Tensorflow - a Practical Guide and Undocumented Features_: Going over some of the best practices for working with RNNs in TensorflowRNN / LSTM cell example in TensorFlow and Python_: Covering how to code a Recurrent Neural Network model with an LSTM in TensorFlowSequence prediction using recurrent neural networks(LSTM) with TensorFlow_: How to approximate a sequence of vectors using a recurrent neural networksTensorFlow RNN Tutorial_: Recurrent Neural Networks for exploring time series and developing speech recognition capabilities
.. _Recurrent Neural Networks: https://www.tensorflow.org/tutorials/recurrent .. _How to build a Recurrent Neural Network in TensorFlow: https://medium.com/@erikhallstrm/hello-world-rnn-83cd7105b767 .. _Recurrent Neural Networks in Tensorflow: https://r2rt.com/recurrent-neural-networks-in-tensorflow-i.html .. _RNNs in Tensorflow - a Practical Guide and Undocumented Features: http://www.wildml.com/2016/08/rnns-in-tensorflow-a-practical-guide-and-undocumented-features/ .. _RNN / LSTM cell example in TensorFlow and Python: https://pythonprogramming.net/rnn-tensorflow-python-machine-learning-tutorial/ .. _Sequence prediction using recurrent neural networks(LSTM) with TensorFlow: http://mourafiq.com/2016/05/15/predicting-sequences-using-rnn-in-tensorflow.html .. _TensorFlow RNN Tutorial: https://svds.com/tensorflow-rnn-tutorial/
Deep Learning with Neural Networks and TensorFlow_: Recurrent Neural Networks (RNN)An Introduction to LSTMs in Tensorflow_: A brief tutorialDeep Learning with Tensorflow - The Recurrent Neural Network Model_: A tutorial on the Recurrent Neural Network ModelsSequence Models and the RNN API_: TensorFlow Dev Summit 2017RNN Example in Tensorflow_: A quick tutorial
.. _Deep Learning with Neural Networks and TensorFlow: https://www.youtube.com/watch?v=hWgGJeAvLws .. _An Introduction to LSTMs in Tensorflow: https://www.youtube.com/watch?v=l4X-kZjl1gs .. _Deep Learning with Tensorflow - The Recurrent Neural Network Model: https://www.youtube.com/watch?v=C0xoB8L8ms0&t=89s .. _Sequence Models and the RNN API: https://www.youtube.com/watch?v=RIR_-Xlbp7s .. _RNN Example in Tensorflow: https://www.youtube.com/watch?v=dFARw8Pm0Gk
Autoencoders
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Deep Autoencoder with TensorFlow_: An open source projectVariational Autoencoder in TensorFlow_: A tutorial on Variational AutoencoderDiving Into TensorFlow With Stacked Autoencoders_: A nice brief tutorialsConvolutional Autoencoders in Tensorflow_: Implementing a single layer CAEVariational Autoencoder using Tensorflow_: Facial expression low dimensional embedding
.. _Deep Autoencoder with TensorFlow: https://github.com/cmgreen210/TensorFlowDeepAutoencoder .. _Variational Autoencoder in TensorFlow: https://jmetzen.github.io/2015-11-27/vae.html .. _Diving Into TensorFlow With Stacked Autoencoders: http://cmgreen.io/2016/01/04/tensorflow_deep_autoencoder.html .. _Convolutional Autoencoders in Tensorflow: https://pgaleone.eu/neural-networks/deep-learning/2016/12/13/convolutional-autoencoders-in-tensorflow/ .. _Variational Autoencoder using Tensorflow: http://int8.io/variational-autoencoder-in-tensorflow/
Deep Learning with Tensorflow - Autoencoder Structure_: Tutorial on Autoencoder modelsDeep Learning with Tensorflow - RBMs and Autoencoders_: Tutorial on Restricted Boltzmann machines and AEs
.. _Deep Learning with Tensorflow - Autoencoder Structure: https://www.youtube.com/watch?v=H_Bi_PQWJJc .. _Deep Learning with Tensorflow - RBMs and Autoencoders: https://www.youtube.com/watch?v=FsAvo0E5Pmw
Generative models
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Generative Adversarial Nets in TensorFlow_: Implementing GAN using TensorFlow, with MNIST dataGenerative Adversarial Networks_: A working example of Generative Adversarial Networks
.. _Generative Adversarial Nets in TensorFlow: http://wiseodd.github.io/techblog/2016/09/17/gan-tensorflow/ .. _Generative Adversarial Networks: http://edwardlib.org/tutorials/gan
TensorFlow Tutorial - Adversarial Examples_: A tutorial on a working example for generative models
.. _TensorFlow Tutorial - Adversarial Examples: link
Multiple GPUs
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Using GPUs_: Official TensorFlow documentationDeep Learning with Multiple GPUs on Rescale_: TensorFlow Tutorial
.. _Using GPUs: https://www.tensorflow.org/tutorials/using_gpu .. _Deep Learning with Multiple GPUs on Rescale: https://blog.rescale.com/deep-learning-with-multiple-gpus-on-rescale-tensorflow/
=================== TensorFlow Projects
This section is dedicated to provide resources that are mainly open source projects developed by TensorFlow. Those might be comprehensive tutorials on working example.
Comprehensive Tutorials
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TensorFlow-World_: Concise and ready-to-use TensorFlow tutorials with detailed documentationTensorFlow-Tutorials_: Introduction to deep learning based on Google's TensorFlow frameworkTensorFlow Tutorials_: Organized tutorials in TensorFlowTensorFlow-Examples_: Providing working examples in TensorFlowTensorflow Tutorials using Jupyter Notebook_: TensorFlow tutorials written in Python plus Jupyter Notebook
.. _TensorFlow-World: https://github.com/astorfi/TensorFlow-World .. _TensorFlow-Tutorials: https://github.com/nlintz/TensorFlow-Tutorials .. _TensorFlow Tutorials: https://github.com/Hvass-Labs/TensorFlow-Tutorials .. _TensorFlow-Examples: https://github.com/aymericdamien/TensorFlow-Examples .. _Tensorflow Tutorials using Jupyter Notebook: https://github.com/sjchoi86/Tensorflow-101
Models
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TensorFlow Models_: Machine learning models implemented in TensorFlowTensorflow VGG16 and VGG19_: Implementation of VGG 16 and VGG 19 based on tensorflow-vgg16 and Caffe to TensorflowResNet in TensorFlow: Implementation ofDeep Residual Learning for Image Recognition <https://arxiv.org/abs/1512.03385>Inception in TensorFlow_: Train the Inception v3 architectureA TensorFlow implementation of DeepMind WaveNet paper: TensorFlow implementation of theWaveNet generative neural network architecture <https://deepmind.com/blog/wavenet-generative-model-raw-audio/>for audio generation3D Convolutional Neural Networks for Speaker Verification: Implementation of3D Convolutional Neural Networks for Speaker Verification application <https://arxiv.org/abs/1705.09422>in TensorFlow.Domain Transfer Network (DTN): The implementation ofUnsupervised Cross-Domain Image Generation <https://arxiv.org/abs/1611.02200>in TensorFlowNeural Style_: The Neural Style algorithm implementation that synthesizes a pasticheSqueezeNet in TensorFlow_: Tensorflow implementation of SqueezeNet
.. _TensorFlow Models: https://github.com/tensorflow/models .. _Tensorflow VGG16 and VGG19: https://github.com/machrisaa/tensorflow-vgg .. _ResNet in TensorFlow: https://github.com/ry/tensorflow-resnet .. _Inception in TensorFlow: https://github.com/tensorflow/models/tree/master/inception .. _A TensorFlow implementation of DeepMind WaveNet paper: https://github.com/ibab/tensorflow-wavenet .. _3D Convolutional Neural Networks for Speaker Verification: https://github.com/astorfi/3D-convolutional-speaker-recognition .. _Domain Transfer Network (DTN): https://github.com/yunjey/domain-transfer-network .. _Neural Style: https://github.com/cysmith/neural-style-tf .. _SqueezeNet in TensorFlow: https://github.com/vonclites/squeezenet
=================== Published Resources
This section is dedicated to provide published resources on TensorFlow, Such as websites, blogs, and books.
Online Courses and Documentations
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LearningTensorFlow_: Beginner-level tutorials for a TensorFlowDeep Learning by Google_: A free online course developed by Google and UdacityTensorflow for Deep Learning Research_: A comprehensive course by StanfordCreative Applications of Deep Learning with TensorFlow_: A free online course on TensorFlow from KadenzeDeep Learning with TensorFlow Tutorial_: In this TensorFlow course, you will be able to learn the basic concepts of TensorFlow
.. _LearningTensorFlow: https://learningtensorflow.com/ .. _Deep Learning by Google: https://www.udacity.com/course/deep-learning--ud730 .. _Tensorflow for Deep Learning Research: https://web.stanford.edu/class/cs20si/ .. _Creative Applications of Deep Learning with TensorFlow: https://www.kadenze.com/courses/creative-applications-of-deep-learning-with-tensorflow/info .. _Deep Learning with TensorFlow Tutorial: https://cognitiveclass.ai/courses/deep-learning-tensorflow/
Books
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TensorFlow Machine Learning Cookbook_: Quick guide to implementing TensorFlow in your day-to-day machine learning activitiesDeep Learning with TensorFlow_: Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systemsFirst contact with TensorFlow_: An online book on TensorFlowBuilding Machine Learning Projects with TensorFlow_: Learn how to implement TensorFlow in productionLearning TensorFlow_: This book is an end-to-end guide to TensorFlowMachine Learning with TensorFlow_: Tackle common commercial machine learning problems with Google’s TensorFlow libraryGetting Started with TensorFlow_: An easy-to-understand book on TensorFlowHands-On Machine Learning with Scikit-Learn and TensorFlow_: By using examples, theory, the book help to gain an understanding of the machine learning conceptsMachine Learning with TensorFlow (MEAP)_: An introduction to the concepts of TensorFlow
.. _TensorFlow Machine Learning Cookbook: https://www.amazon.com/dp/B01HY3TC54/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1 .. _Deep Learning with TensorFlow: https://www.packtpub.com/big-data-and-business-intelligence/deep-learning-tensorflow .. _First contact with TensorFlow: http://jorditorres.org/first-contact-with-tensorflow/ .. _Building Machine Learning Projects with TensorFlow: https://www.amazon.com/dp/B01M2Z8FS4/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1 .. _Learning TensorFlow: http://shop.oreilly.com/product/0636920063698.do .. _Machine Learning with TensorFlow: https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-tensorflow .. _Getting Started with TensorFlow: https://www.amazon.com/Getting-Started-TensorFlow-Giancarlo-Zaccone-ebook/dp/B01H1JD6JO .. _Hands-On Machine Learning with Scikit-Learn and TensorFlow: http://shop.oreilly.com/product/0636920052289.do .. _Machine Learning with TensorFlow (MEAP): https://www.manning.com/books/machine-learning-with-tensorflow
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Repo liên quan
TensorFlow is Google's open-source, end-to-end platform for machine learning, hosted at tensorflow/tensorflow under the Apache-2.0 license. It was originally built within Google Brain's Machine Intelligence team for ML and neural network research, and today it ships stable Python and C++ APIs alongside GPU, CPU-only, and Docker install paths. The README positions it as covering both research work and shipping ML-powered applications.
Hugging Face Transformers (huggingface/transformers) is a Python library that centralizes model definitions for text, computer vision, audio, video, and multimodal machine learning, covering both inference and training. The README describes it as a pivot point compatible with training frameworks such as Axolotl, DeepSpeed, and PyTorch-Lightning, and inference engines such as vLLM, SGLang, and TGI, with more than 1M+ model checkpoints listed on the Hugging Face Hub.
PyTorch is an open-source Python package hosted at pytorch/pytorch on GitHub, built around two core capabilities: NumPy-like Tensor computation with GPU acceleration, and deep neural networks built through a tape-based autograd system. Its components include torch.nn for network layers, torch.jit for compiling models into TorchScript, and torch.multiprocessing for sharing Tensors across processes, with build support for CUDA, AMD ROCm, and Intel GPU backends documented in the README.
LLMs-from-scratch is Sebastian Raschka's GitHub companion to the Manning book Build a Large Language Model (From Scratch), ISBN 9781633437166. It walks through building, pretraining, and finetuning a GPT-style model in PyTorch across seven chapters and five appendices, plus a growing set of bonus notebooks covering newer open architectures.
Trả lời nhanh
Cùng nhóm AI Tools còn repo nào?
instillai/TensorFlow-Roadmap thuộc nhóm AI Tools trên TopGit, cùng 5 topic GitHub. Trang Trending và Topics liệt kê các repo cùng số sao và cùng ngôn ngữ để so sánh.
Đọc thêm về instillai/TensorFlow-Roadmap ở đâu?
Trang TopGit này là một snapshot — tab "Readme" hiển thị nguyên văn README của repo (đã bỏ link, giữ ảnh). Repo GitHub ở github.com/instillai/TensorFlow-Roadmap là nguồn chính thức.
instillai/TensorFlow-Roadmap có bao nhiêu sao?
instillai/TensorFlow-Roadmap có 87 sao GitHub — tải lại trang để xem số mới nhất, hoặc xem trực tiếp github.com/instillai/TensorFlow-Roadmap. TopGit phản chiếu số sao của GitHub nhưng không cam kết đến từng phút.
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TopGit chưa ghi nhận license cho instillai/TensorFlow-Roadmap. Phần lớn repo public trên GitHub là mã nguồn mở, nhưng điều khoản khác nhau từng repo — mở file LICENSE để xác nhận.
instillai/TensorFlow-Roadmap có trang demo không?
Dự án có trang chủ ở http://www.machinelearningmindset.com/tensorflow-roadmap-ebook/. Tab "Readme" ở trang này thường có ảnh chụp và hướng dẫn bắt đầu nhanh.
instillai/TensorFlow-Roadmap là gì?
instillai/TensorFlow-Roadmap (instillai/TensorFlow-Roadmap) là dự án Python trên GitHub. Theo mô tả gốc: :satellite: Organized & Useful Resources about Deep Learning with TensorFlow
instillai/TensorFlow-Roadmap so với các dự án AI Tools khác thế nào?
instillai/TensorFlow-Roadmap được TopGit xếp vào nhóm AI Tools, với 87 sao GitHub và viết bằng Python. Xem trang chủ đề AI Tools trên TopGit để so sánh với các dự án tương tự theo số sao và mức độ hoạt động.
Đọc đầy đủ README ở tab phía trên.
Vẫn đang phân vân về TensorFlow-Roadmap?
Một cú bấm sẽ gửi câu hỏi kèm trang này cho AI — xem AI nói gì về TensorFlow-Roadmap.