PROGRAM DETAILS

Course

Training & Internship - Deep Learning with TensorFlow

3 months

PROGRAM DETAILS

This course will cover the fundamentals and contemporary usage of the TensorFlow library for deep learning research. We aim to help students understand the graphical computational model of TensorFlow, explore the functions it has to offer, and learn how to build and structure models best suited for a deep learning project. Through the course, students will use TensorFlow to build models of different complexity, from simple linear/logistic regression to convolutional neural network and recurrent neural networks to solve tasks such as word embedding, translation, optical character recognition, reinforcement learning. Students will also learn best practices to structure a model and manage research experiments.

 

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.

 

 

 Duration   

 

 3 Months   

 

 Upcoming   Batch date   

 

 08, June 2019  (Weekend Saturday/Sunday Batch)  

 

 Training   Options   

 

 

 Timings for online class

   

 3 hours Online class sessions on Saturdays & Sundays [Class timings: 2 pm - 5 pm]

 

 

 Administrative 
 Fees     

 

 

 Rs. 19,980/-  or  Rs. 6,660/- * 3 Installments 

 

 

 

 Contact   

 

 

 Please call Naveen at +91 79944 28133 to confirm your registration.

 

 

 Target   Audience   

 

 

 IT Professionals:- Those who would like to switch their field or upgrade their skills in ML and Data Science.

 Students :- Those who aspire to form their career in the field of AI

 Anyone Who love Data Science and AI

 Prerequisites 

 

 Proficiency in Python:


All class assignments will be in Python. There is a tutorial here for those who aren't as familiar with Python. If you have a lot of programming experience but in a different language (e.g. C/C++/Matlab/Javascript), you will probably be fine.

 

 Knowledge in Machine Learning:


We will not ask you to take derivatives or build your own optimizers, but you should know what they are and how to use them.


 Basic Theoretical Understanding of Neural Networks:


This course focuses more on the practical usage of Tensorflow in deep learning projects, therefore you can benefit more from the course if you already have basic understanding of neural networks: feed-forward, convnet, LSTM, sequence to sequence model.

 

 

 

Course Content


Setup and Installation of Tensorflow for Python 

Overview of Tensorflow:

Why Tensorflow?
Graph and Session

Operations:

Basic operations, constants, variables 
Control dependencies 
Data pipeline 
TensorBoard 

Linear and Logistic Regression

Tensorflow's Optimizers 
tf.data
Example: Birth rate - life expectancy, MNIST dataset

Eager Execution

Example: word2vec, linear regression


Variable sharing and managing experiments

Interfaces 
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

Dialogue Agents

Reinforcement Learning with Tensorflow

Keras- A wrapper to Tensorflow Framework

 

Internship Project:

 

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.

 

Recorded videos:

 

 

 

 

 

 

 

 

Next steps?

 

If you would like to join this program please register below:

 

REGISTER FOR THIS PROGRAM