$200!! 2 Day Artificial Intelligence and Deep Learning Training at Eruditio...

Event Information

Share this event

Date and Time



International Technological University

2711 North First Street

San Jose, CA 95134

View Map

Refund Policy

Refund Policy

Refunds up to 1 day before event

Event description


2 day Deep Learning and AI Training Erudition Inc.

Erudition Inc. is offering AI Deep Learning training on December 8-9 2018.

Our mission: Erudition Inc.'s mission is to provide education in emerging technologies to masses at no cost or very affordable rate. What is life's objective at the end of the day? Life is fleeting, and permanence in this world is something we all strive for. The best way to achieve permanence is through sharing knowledge.

Doesn't matter if you are aligned to left brain or right brain you can join Erudition in your Emerging Technologies training!! We will also provide interview help and placement services.

You will get USD300.00 worth of books for Free!! That are written by Bhairav Mehta and other authors.

Time Date : December 8-9 2018 8AM to 6PM

Location: International Technological University, 2711 North First Street, San Jose CA 95134

Instructor: Bhairav Mehta

Bhairav Mehta is Data Science Manager at Apple Inc. He has 15 years experience in Analytics and Data Science space at various fortune 100 companies. Bhairav Mehta is academician and tenured faculty at various Bay area Universities. Bhairav Mehta has taught 1000s of students in AI, ML and Big Data technologies over last 5 years. He also gives talks at Association of Computing Machinery (ACM), IEEE Computer Science society, Global Big Data and AI conferences, Open Data science conference and other forums. Bhairav Mehta has 5 graduate degrees from top institutes: MS Computer Science (GeorgiaTech), MBA (Cornell University), MS Statistics (Cornell University) etc.

Linkedin Profile: https://www.linkedin.com/in/mehtabhairav/­

Erudition Website: http://www.eruditionsiliconvalley.com

Bhairav Mehta talk videos and other conference proceedings: https://bit.ly/2MrMbGV­

What is this course about?

What do web search, speech recognition, face recognition, machine translation, autonomous driving, and automatic scheduling have in common? These are all complex real-world problems, and the goal of artificial intelligence (AI) is to tackle these with rigorous mathematical tools. In this course, you will learn the foundational principles that drive these applications and practice implementing some of these systems. Specific topics include machine learning, search, game playing, Markov decision processes, constraint satisfaction, graphical models, and logic. The main goal of the course is to equip you with the tools to tackle new AI problems you might encounter in life.


Day 1

  1. Overview and Introduction

  2. Introduction to Neural Networks

  3. Current /Future Industry Trends

  4. Your First Neural Network

  5. Google Colab Cloud Platform Intro and Set up

  6. ML introduction

  7. Gradient Descent, Error function

  8. Training Neural Network

  9. Tensorflow, Keras, Theano, Lasagne, Torch, Caffe introduction

  10. Tensorflow Labs

  11. Tensorflow and Keras labs for simple classification and clustering. Supervised and unsupervised.

  12. Regularization Intro

  13. Neural Network Architecture and Hyper Parameter tuning

  14. Convolution Neural Network

  15. Labs with Tensorflow and CNN, CNN with Regularization

  16. CNN in Tensorflow

  17. Weight Initialization

  18. Auto Encoders

  19. Transfer Learning

  20. ImageNet, LeNet, Alexnet, VGGNet, Inception, ResNet

  21. Object Detection

  22. Auto Encoder and Transfer learning labs

  23. Image Segmentation

  24. Face Detection

  25. Image Classification

  26. Labs with Keras and TensorFlow

Day 2

  1. Advanced Object Detection methods: R-CNN, F R-CNN, YOLO, Mask R-CNN, Labs

  2. Labs for Image Classification

  3. Labs for Image Segmentation and Face detection

  4. Recurrent Neural Network Intro (RNN)

  5. Long Short term Memory (LSTM)

  6. Motivation for learning RNN and LSTM

  7. Simple RNN and LSTM labs for Time Series

  8. Cloud based tools for doing object detection, image classification and applications of CNN

  9. RNN-LSTM Labs continued

  10. Natural Language Processing (NLP)

  11. Work2Vec, Word Embedding, PCA and T-SNE for Word Embedding

  12. NLP Labs

  13. Sequence to Sequence LSTM Chatbots and LSTM based Text Generation

  14. Review and Introduction to advanced concepts in Neural Networks e.g. Reinforcement Learning, Generative Adversarial Networks, Autonomous Driving car etc.

Intended Audience

Programmers, analysts, managers, investors, enthusiast pretty much anyone technically curious about deploying Machine Learning.


Deep Learning

An MIT Press book

Ian Goodfellow and Yoshua Bengio and Aaron Courville



Other Reading Material:

Slides (To be delivered separately)

Following material will be provided by Bhairav Mehta (It is worth USD300.00)

4 workshop guides will be provided

  • Deep Learning and Python CNN

  • Deep Learning and Natural Langugage Processing

  • LSTM and RNN

Each topic includes codes and explanation step-by-step


Bhairav Mehta

URL: http://www.eruditionsiliconvalley.com

Phone# 4086608118

Email: eruditionbayarea@gmail.com

Date and Time


International Technological University

2711 North First Street

San Jose, CA 95134

View Map

Refund Policy

Refunds up to 1 day before event

Save This Event

Event Saved