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MLTrain is coming back to NY for another training event. Nick Vasiloglou and Alex Dimakis will cover several Machine Learning and TensorFlow topics. We have prepared a 2 day curriculum. You can register for each day individually or for both days. The space is offered by Ebay! When: 6/2-6/3 2017, 9:00am to 2:00pm Where: 625 6th Ave (between 18th & 19th), 3rd floor , New York, NY (Ebay) Discount code mltrain_15 for 15% with your datascience team

MLTrain 6/2/2017

Introduction to TensorFlow and Keras

This session is intended for beginners. The only requirements are:

  • Be familiar with python programming

  • Be able to install tensorFlow before the class date

  • Be familiar with basic Machine Learning Principles

After the completion of the session you will know the basic functionality of TensorFlow. You will be able to build simple models and also use it in data science projects. 

Introduction to TensorFlow 

  • MLTrain Introduction

  • Tensors Basics

  • Computational Graph Model

  • Graph Inspection & Visualization with TensorBoard

  • Basic Ops

Linear Algebra

  • Fundamentals of  Linear Algebra

  • Least Square Problem

  • Manipulating Matrices in TensorFlow

  • Sparse/Dense Matrix/Vectors Operations

  • Limitations of TF

Optimization In TensorFlow

  • Objective Function

  • Gradients Computation

  • The tf.Optimizer Class

  • Predefined Optimizers

  • TF Linear Regression Model In 3 Lines

  • Predefined Losses

Introduction to Neural Networks

  • Fundamentals of Neural Nets

  • The back propagation algorithm

  • Convolutional Nets

  • Recurrent Neural Nets

  • Applications

 MLTrain 6/3/2017 

Deep Learning  Applications 

 In this session you will learn how to use TensorFlow for building deep learning models for different application domains. The session emphasizes understanding models, how to use them and when to trust them. 

In order to attend this session you are expected:

  • To have basic knowledge of TensorFlow. You can do that by going through the tutorials in the 

  • To be proficient in python

  • To have tensorFlow already installed on your machine

  • To have some data science prior experience or exposure  

 Working with Images

  • Understanding and using Generative Models

  • The Generative Adversarial Network (GAN)

  • Applications of GANs

Working with Text

  • Word2Vec

  • LSTMs for parsing Text

 Deep Reinforcement Learning

  • Encoding Agents for playing Games

  • Policy learning

MLTrain 6/3/2017 

Advanced Deep Learning topics 

(Not Final Yet)

Tell us about the topics you are interested in. Fill out the form

  • Pixel Recurrent Neural Networks

  • Memory  Networks 

  • Learning to Discover Cross-Domain Relations with Generative Adversarial Networks

  • Value Iteration Networks

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Blog Publisher / Head of Data Science Search

Founder & Head of Data Science Search at Starbridge Partners, LLC.