Training & Internship - Deep Learning with TensorFlow
TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google. It has many pre-built functions to ease the task of building different neural networks. TensorFlow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a single machine. TensorFlow provides a Python API, as well as a less documented C++ API. For this course, we will be using Python.
Setup and Installation of Tensorflow for Python
Overview of Tensorflow:
Graph and Session
Basic operations, constants, variables
Linear and Logistic Regression
Example: Birth rate - life expectancy, MNIST dataset
Example: word2vec, linear regression
Variable sharing and managing experiments
Name scope, variable scope
Saver object, checkpoints
Autodiff Example: word2vec
Introduction to ConvNet
Example: Image classification
Generative Neural Networks (GAN’s)
Variational Auto encoder
Recurrent Neural Networks
Example: Character-level Language Modeling
Seq2Seq with Attention
Example: Neural Machine Translation
Reinforcement Learning with Tensorflow
Keras- A wrapper to Tensorflow Framework
Deep Learning with TensorFlow project using Industrial Application
Key Takeaways from the course:
Cutting edge coding skills for Machine Learning
Assignments and Workshops every Week.
Hands on Industrial project use case at the end of the course.
Certification after learning all the Assignment and Workshops.
Placement and Internship Opportunities.
If you would like to join this program please register below: