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 TensorFlow? Introduction, Architecture & Example
Tutorial How to Download and Install TensorFLow Windows and Mac
Tutorial What is Jupyter Notebook? Complete Tutorial
Tutorial TensorFlow Basics: Tensor, Shape, Type, Graph, Sessions & Operators
Tutorial Tensorboard Tutorial: Graph Visualization with Example
Tutorial Python Pandas Tutorial: Dataframe, Date Range, Slice
Tutorial Import CSV Data using Pandas.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
Tutorial Expert System in Artificial Intelligence: What is, Applications, Example
Tutorial TensorFlow Tutorial PDF