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Machine Learning In Javascript With Tensorflow Js




Java Certification Course


All Job Seekers


Both Classroom and Online Classes


Week Days and Week Ends

Duration :

45 Days

Java Objectives

•How To resolve errors in Java.
•How to create delete and view Java.
•You will know how to work with Java.
•Build deploy and run your Java configuration and code.
•Learn Java from scratch & understand core programming concept
•Discuss all the principles of Java and demonstrate though Assignment.
•Learn Basic and Advanced Java Programming and become a Java Developer
•Learn Java. Become Developer in Test and Kick-start your Career in IT.
•Learn Java Complete Course with Professionals from Scratch and Become a Pro in Java

machine learning in javascript with tensorflow js Training Features

•24 × 7 = 365 days supportive faculty
•Resume & Interviews Preparation Support
•Job Placement Assistance with Good Companies
•Online Training with 100% placement assistance
•Highly Experienced Trainer with 10+ Years in MNC Company
•Project manager can be assigned to track candidates’ performance
•Live project based on any of the selected use cases, involving implementation of the concepts
• Our dedicated HR department will help you search jobs as per your module & skill set, thus, drastically reducing the job search time

Who are eligible for Java

•Angularjs, Core Java, .Net, Ui Development, Ssis, Ssrs, Mobility Architect, Java Architect, Devops, Android Developer, Ios Developer
•Hyperion Developer, Hyperion Essbase, OBIEE, Oracle BI, Oracle Business Intelligence, Data Warehouse, Oracle Apps Funcitional, Oracle Apps HRMS Technical
•Java Programmer, Ui Designer, Web Developer, Web Designer, Automation Testing, graphic designer visualiser, java script frameworks, PHP
•Qa Testers / Developers, Full Stack Developers – Backend / Frontend, Power Bi, Market Intelligence
•Storage Domain Professionals, SAN, NAS, Devops Engineer, Developer – Storage Domain, File System, Storage Domain, RAID, CIFS, NFS, Linux, Kernel Programming


•Updated for 2020!
•Interested in using Machine Learning in JavaScript applications and websites? Then this course is for you!
•This is the tutorial you’ve been looking for to become a modern JavaScript machine learning master in 2020. It doesn’t just cover the basics, by the end of the course you will have advanced machine learning knowledge you can use on you resume. From absolute zero knowledge to master – join the TensorFlow.js revolution.
•This course has been designed by a specialist team of software developers who are passionate about using JavaScript with Machine Learning. We will guide you through complex topics in a practical way, and reinforce learning with in-depth labs and quizzes.
•Throughout the course we use house price data to ask ever more complicated questions; “can you predict the value of this house?”, “can you tell me if this house has a waterfront?”, “can you classify it as having 1, 2 or 3+ bedrooms?”. Each example builds on the one before it, to reinforce learning in easy and steady steps.
•Machine Learning in TensorFlow.js provides you with all the benefits of TensorFlow, but without the need for Python. This is demonstrated using web based examples, stunning visualisations and custom website components.
•This course is fun and engaging, with Machine Learning learning outcomes provided in bitesize topics:
•Part 1 – Introduction to TensorFlow.js
•Part 2 – Installing and running TensorFlow.js
•Part 3 – TensorFlow.js Core Concepts
•Part 4 – Data Preparation with TensorFlow.js
•Part 5 – Defining a model
•Part 6 – Training and Testing in TensorFlow.js
•Part 7 – TensorFlow.js Prediction
•Part 8 – Binary Classification
•Part 9 – Multi-class Classification
•Part 10 – Conclusion & Next Steps
•Who this course is for:
•Introduction: What is TensorFlow.js?
•Course Overview
•Machine Learning Concepts
•Overview of Artificial Neural Networks
•Lab: TensorFlow Playground
•TensorFlow.js and Machine Learning
•Installing and running TensorFlow.js
•TensorFlow.js environments
•Running TensorFlow.js in the browser
•WebGL optimisations in TensorFlow.js
•Running TensorFlow.js on Node.js
•New: TensorFlow.js for React Native
•Lab: Install and run TensorFlow.js in the browser
•Lab: Install and run TensorFlow.js on Node.js
•TensorFlow environments and installation
•TensorFlow.js Core Concepts
•TensorFlow.js APIs
•What is a Tensor?
•Tensor Math Operations & Ops API
•Memory Management in TensorFlow.js
•Lab: Tensor Math and Memory Management
•TensorFlow.js math and memory
•Data Preparation with TensorFlow.js
•Linear Regression
•Reading data from CSV
•Visualising the data
•Preparing Features and Labels
•Normalisation with TensorFlow.js
•Splitting into Training and Testing data
•Lab: Prepare the Data
•Data Preparation
•Defining a model
•Introduction to Layers API
•Creating Layers in TensorFlow.js
•Inspecting a TensorFlow.js model
•Compiling the model
•Lab: Creating a Model
•TensorFlow.js Models
•Training and Testing in TensorFlow.js
•Introduction to Training and Testing
•Training with
•Visualising loss with tfjs-vis
•Testing with model.evaluate
•Training and testing: review & lab
•Lab: TensorFlow.js Training and Testing
•Training and Testing
•TensorFlow.js Prediction
•Integrating TensorFlow.js with a UI
•Saving and loading a model
•Making Predictions
•Visualising Predictions
•Non-linear Regression
•Prediction: review & labs
•Lab: TensorFlow.js predictions
•TensorFlow.js predictions
•Lab: Beyond Linear Regression
•Lab (optional): Training without Layers API
•Binary Classification
•Introduction: Binary Classification
•Visualising Classification Data
•Preparing Multiple Features
•Binary Classification Model
•Visualising Classification with Heatmaps
•Binary Classification Predictions
•Binary Classification: Review & Lab
•Lab: TensorFlow.js Binary Classification
•Quiz: Binary Classification
•Multi-class Classification
•Introduction: Multi-class Classification
•One hot encoding
•Multi-class classification model
•Visualising Multi-class Predictions
•Multi-class prediction
•Multi-class Classification: Review & Lab
•Lab: TensorFlow.js Multi-class Classification
•Conclusion & Next Steps
•Course Review
•Next steps with TensorFlow.js
•Resources for going deeper with TensorFlow.js