Develop Real-Time practical
DApps using Ethereum and
JavaScriptds

Build DApps using Solidity and Web3.js

Create Ethereum wallets, Explore consortium blockchain

DAOs, Decentralized autonomous organizations, are capable of running themselves thanks to blockchain technology

No CEO needed: These blockchain platforms will let ‘the crowd’ run startups

Blockchain is a technological
advancement that will transform
financial services and other
industries as well.

Learn to Build Decentralized Applications on Blockchain

new-test2018-02-06T01:10:47+00:00

Project Description

Deep Learning Class room

Deep Learning In-Class Bootcamp

Face Recognition

Fully Immersive and Evening Bootcamps

Artificial Intelligence Online Training

Online Live Instructor-Led Sessions

Artificial Intelligence

Build Artificial Intelligence Algorithms

Live Instructor-Led Online or In-Class Sessions

Hands-On Live Instructor-led sessions | Workshops | Real-world Scenarios on BigDataGuys cloud platform | Upto 100 GPUs Cloud Computing Power

Instructors from Google | Uber | Mckinsey | Nvidia | Facebook | Intel | IBM

Online or Class room bootcamp

How does bootcamps work?

There’s two kinds of bootcamps.

A. Live instructor-led training conducted on Webex software with built-in video and screen sharing options. Please note that this is not a recorded version of training.

B. In-Class at a physical location in major cities such as NYC, D.C, Philadelphia, Chicago, Austin, Dallas, Denver, Bay are etc..

  • Entirely based on Projects & Use Cases – End to End Live Project Implementation

  • Access to Deep Learning Cloud Platform – Upto 100 GPU computing power, hundreds of large size data sets

  • Over fifty deep learning use cases- Candidates have an option to choose up to three use cases during the training

  • Instructors from fortune 500 – Google, Uber, Nvidia, Facebook, Intel, IBM Watson etc..

Deep Learning Training

Objective of the course

This course is designed to teach you how to build deep-learning models to detect what a driver is doing in a car given the driver’s images. The model will automatically detect, with high accuracy, drivers engaged in distracted behaviors by applying convolutional neural network (CNN) and this will be done using the Python programming language. Distracted drivers are quietly causing a staggering amount of serious car accidents. In fact, driver distractions are the leading cause of most auto accidents. As experienced car accident lawyers in San Diego, we have handled plenty of automobile accidents that were caused by driver distractions or driver inattentiveness.

Here are some common driver distractions:

  • Talking on a cell phone
  • Sending text messages
  • Drinking
  • Reaching for a moving object inside the vehicle
  • Looking at an object or event outside of the vehicle
  • Reading a book
  • Eating food
  • Applying makeup.

Fortunately we can apply deep learning to automatically detect distracted driver using convolutional neural network (CNN, or ConvNet)

Enrol Now

Online $1499

Enrol Now

InClass $4999

Ethereum Blockchain Developera

Blockchain, FINTECH , Ethereum Blockchain
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0
Four Weeks duration | Live Instructor-Led online
0
Eight Weeks | Live online fully immersive
0
Four weeks duration | In-Class Evening Bootcamp
0
8 Weeks duration| In-Class Fully Immersive

Deep Learning Consulting and Capstone Projects Using TensorFlow, Keras, Cafe etc..

Deep Learning and Chatbot

Build Chatbot using sequence-to-
sequence (seq2seq) model 

Click here to review project

Real-time analysis of behaviors

Real-time behavior analysis

Get real-time insights about the behavior of cars, people and potentially other objects

Click here to review project

Energy Market Price Forecasting

Artificial neural network

Build Artifiical Neural Network to Energy Grid in effort to predict usage fluctuations

Click here to review project

Face Keypoint Detection CNN

Computer Vision Open CV

OpenCV Faced recognition and segmentation 

Click here to review project

A Neural Conversational Model

Natural Language Processing

Recurrent Neural Network 

Click here to review project

Natural Language Processing Chatbot

NLP

Creative Applications of Deep Neural Network

Click here to review project

Our client partner network

Locations

116 West 23rd Street 5th Floor New York City, NY 10011

Manhattan, NY

Washington, D.C (Dupont Circle)

1875 Connecticut Ave NW 10th Floor Washington DC 20009

San Fransisco, CA (Civic Center)

1161 Mission St San Francisco CA 94103

San Fransisco, CA

Washington, D.C

Tysons, Virginia

1775 Tysons Blvd Tysons VA 22102

CONTACT INFO

Main Office: 1250 Connecticut Avenue NW, Washington,

Phone: 202-897-1944 | 202-897-1966

For Training: [email protected]

For Consulting: [email protected]

Need help? Message us










Big Data
Artifiicial Intelligence
Blockchain-Hyperledger
Cloud
Custom Software
Federal ERP


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