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Training Summary

Google's TensorFlow is an open-source and most popular deep learning library for research and production. This course covers basics to advance topics like linear regression, classifier, create, train and evaluate a neural network like CNN, RNN, auto encoders etc. Refer these machine learning tutorial, sequentially, one after the other, for maximum efficacy of learning.

What should I know?

The online guide is designed for beginners with little or no TensorFlow Experience. Though basic understanding of Python is required.

Course Syllabus

Tutorial What is AI? Artificial Intelligence Tutorial
Tutorial What is Machine Learning? A Beginners Tutorial
Tutorial What is Deep learning? A Beginner's Tutorial
Tutorial Machine Learning vs Deep Learning: What's the Difference?
Tutorial What is TensorFlow? Introduction, Architecture & Example
Tutorial Deep Learning Libraries: TenserFlow Vs Theano Vs Torch Vs Keras
Tutorial How to Download and Install TensorFLow Windows and Mac
Tutorial What is Jupyter Notebook? Complete Tutorial
Tutorial How to use Jupyter Notebook with AWS and Docker
Tutorial TensorFlow Basics: Tensor, Shape, Type, Graph, Sessions & Operators
Tutorial Tensorboard Tutorial: Graph Visualization with Example
Tutorial NumPy Tutorial: Learn with Example
Tutorial Pandas Tutorial: Dataframe, Date Range, Slice, Groupby, Import(read_csv)
Tutorial Linear Regression with TensorFlow [Examples]
Tutorial Linear Regression for Machine Learning
Tutorial Linear Classifier in TensorFlow: Binary Classification Example
Tutorial Kernel Methods in Machine Learning: Gaussian Kernel (Example)
Tutorial Neural Network Tutorial: TensorFlow ANN Example
Tutorial ConvNet(Convolutional Neural Network): TensorFlow Image Classification
Tutorial Autoencoder in Deep Learning: TensorFlow Example
Tutorial RNN(Recurrent Neural Network) Tutorial: TensorFlow Example
Tutorial Apache Spark Tutorial: Machine Learning with PySpark and MLlib
Tutorial Scikit-Learn Tutorial: Machine Learning in Python