Deep Learning Bootcamps NYC 2017-07-26T01:48:44+00:00

AI Tenser Flow  

Deep Learning Tutorials | Tensorflow Tutorials

AI – Tensor Flow Deep Learning

Deep Learning Bootcamp NYC

Deep Learning Bootcamp

We start off with the basic installation of Tensor flow, moving on to covering the unique features of the library such as Data Flow Graphs, training, and visualization of performance with Tensor Board—all within an example-rich context using problems from multiple sources.

Online: $2,999
Next Session: 14th Aug 2017

TRAINING METHODOLOGY

In Class: $9,999
Locations: NEW YORK CITY, D.C, BAY AREA.
Next Session: 15th Jul 2017

Home / All courses / Advance Deep learning / Deep Learning Tutorials | Tensorflow Tutorials

Deep Learning Tutorials | Tensorflow Tutorials

Instructor: John Doe, Lamar George

DESCRIPTION

Tensorflow with Image recognition

Tensorflow with Image Recognition

Bootcamps/Workshops in NYC, Bay Area and on demand online

Prerequisites: Statistics Python

This course is for Python programmers and data analysts who want to learn more cutting edge machine learning techniques. Students should have basic experience with Python. Students with no prior Python experience can take our 1 week Python programming fast track course which covers sufficient Python for this course.

Artificial intelligence & Deep Learning with tensorflow (convolutional neural networks)

Description

TensorFlow is a 2nd Generation API of Google’s open source software library for Deep Learning. The system is designed to facilitate research in machine learning and to make it quick and easy to transition from research prototype to production system.

Audience:

This course is intended for engineers seeking to use TensorFlow for their Deep Learning projects

Goals:

After completing this course, delegates will understand TensorFlow’s structure and deployment mechanisms

Be able to carry out installation/production environment/architecture tasks and configuration

Be able to assess code quality, perform debugging, monitoring

Be able to implement advanced production like training models, building graphs and logging

AI & Deep learning with Tensorflow course will make you an expert in training and optimize basic and convolutional neural networks using real time projects and assignments. You will also master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM).

  • TensorFlow could be a game-changer in the future of AI – Google
  • Google gives every one machine learning superpowers with TensorFlow
  • Google open-sources TensorFlow for deep learning with big data

Hardware Requirements:

The system requirements for Deep Learning with Tensorflow course is Multicore Processor (i3-i7 series), 8GB of RAM is recommended and 15 GB of free disk space. The operating system can be Windows, Linux or Mac OS X.

Hands-On Sessions (Lab Exercises) –

For executing the practical, you will set-up Tensorflow library on your machine, which can be installed on any operating system that is (Windows, Linux or Mac OS X). The detailed step by step installation guides will be present in your LMS which will help you to install and setup the required environment. In case you come across any doubt, the 24*7 support team will promptly assist you.

Machine learning is one of the fastest-growing and most exciting fields out there, and deep learning represents its true bleeding edge. In this course, you’ll develop a clear understanding of the motivation for deep learning, and design intelligent systems that learn from complex and/or large-scale datasets.

We’ll show you how to train and optimize basic neural networks, convolutional neural networks, and long short term memory networks. Complete learning systems in TensorFlow will be introduced via projects and assignments. You will learn to solve new classes of problems that were once thought prohibitively challenging and come to better appreciate the complex nature of human intelligence as you solve these same problems effortlessly using deep learning methods.

The average salary for deep learning with tensor-flow is $65,885*.

CURRICULUM

MACHINE LEARNING AND RECURSIVE NEURAL NETWORKS (RNN) BASICS

Lecture1.1 NN and RNNLecture1.2

Lecture1.2 Backpropagation

Lecture1.3 Long short-term memory (LSTM)

TENSORFLOW BASICS 

Lecture2.1 Creation, Initializing, Saving, and Restoring TensorFlow variables

Lecture2.2 Feeding, Reading and Preloading TensorFlow Data

Lecture2.3 How to use TensorFlow infrastructure to train models at scale

Lecture2.4 Visualizing and Evaluating models with TensorBoard

TENSORFLOW MECHANICS (ARTIFICIAL INTELLIGENCE)

Lecture3.1 1. Prepare the Data Download Inputs and Placeholders

Lecture3.2 2. Build the Graph Inference Loss Training

Lecture3.3 3 Train the Model The Graph The Session Train Loop

Lecture3.4 4 Evaluate the Model Build the Eval Graph Eval Output

ADVANCED USAGE

Lecture4.1 Threading and Queues

Lecture4.2 Distributed TensorFlow

Lecture4.3 Writing Documentation and Sharing your Model

Lecture4.4 Customizing Data Readers

Lecture4.5 Using GPUs¹

Lecture4.6 Manipulating TensorFlow Model Files

TENSORFLOW SERVING (ARTIFICIAL INTELLIGENCE)

Lecture5.1 Introduction

Lecture5.2 Basic Serving Tutorial

Lecture5.3 Advanced Serving Tutorial

Lecture5.4 Serving Inception Model Tutorial

Online: $3,999
Next Batch: starts from 14th Aug 2017

In Class: $9,999
Locations: New York City, D.C., Bay Area
Next Batch: starts from 17th July 2017

COURSE HIGHLIGHTS

Skill level: Intermediate
Language: English
Certificate: No
Assessments: Self
Prerequisites: Basic Python programming

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FAQ'S

What do I need to know before taking this Course?

A basic understanding of Python and modeling.
Familiarity with matrices and linear algebra.

Does Tensor Flow work with Python 3?

As of the 0.6.0 release timeframe (Early December 2015), it does support Python 3.3+.

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