2 day Deep Learning and AI Training Erudition Inc.

Erudition Inc. is offering AI Deep Learning training on September 28-29 2019.

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 : Sept 28-29 2019 9AM to 6PM

Location: TBD San Jose CA

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.

Schedule:

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. Machine Learning Algorithms and examples of each. Unsupervised and Supervised algorithms
   
   
8. Machine Learning Applications and Usecases

9. Gradient Descent, Error function

10. Training Neural Network

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

12. Tensorflow Labs

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

14. Regularization Intro

15. Neural Network Architecture and Hyper Parameter tuning

16. Convolution Neural Network

17. Labs with Tensorflow and CNN, CNN with Regularization

18. CNN in Tensorflow

19. Weight Initialization

20. Auto Encoders

21. Transfer Learning

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

23. Object Detection

24. Auto Encoder and Transfer learning labs

25. Image Segmentation

26. Face Detection

27. Image Classification

28. 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.

TextBooks:

Deep Learning

An MIT Press book

Ian Goodfellow and Yoshua Bengio and Aaron Courville

http://www.deeplearningbook.org

https://github.com/janishar/mit-deep-learning-book-pdf/blob/master/complete-book-pdf/deeplearningbook.pdf

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

Thanks

Bhairav Mehta

URL: http://www.eruditionsiliconvalley.com

Phone# 4086608118

Email: eruditionbayarea@gmail.com