Corporate Tensorflow.js Training Course

Name: Tensorflow.js Training
Availability: InStock

Edstellar’s Tensorflow.js instructor-led training course offers a comprehensive exploration of integrating machine learning into web development. Upskill your team with the topics such as regression techniques, neural network implementation, and classification methods.

Duration

24 - 32 hrs

Delivery Type

Instructor-led Group Training
(Virtual / On-site / Off-site)

Training Available in

10 Languages

Multiple Locations

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Looking for multiple trainings? Get a detailed quote for group training

About Learning Outcomes Key Benefits Course Outline Target Audience Training Modes Certificate Trainers Request a Training Quote

Drive Team Excellence with Tensorflow.js Corporate Training

TensorFlow.js is an open-source library developed by Google that allows developers to define, train, and run machine learning models directly in the browser or on Node.js servers using JavaScript. TensorFlow.js enables teams to deploy machine learning models directly within web applications. Tensorflow.js training empowers professionals to stay competitive and innovative in the business, where data-driven insights and personalized user experiences are essential for success.

Edstellar's virtual/onsite Tensorflow.js training course provides customization and employs cutting-edge methodologies. Our trainers are recognized for their expertise of the Tensorflow.js instructor-led training course and possess extensive proficiency in handling the intricacies of the platform to develop and deploy machine learning models within web applications.

Get Customized Expert-led Training for Your Teams

Customized Training Delivery

Scale Your Training: Small to Large Teams

In-person Onsite, Live Virtual or Hybrid Training Modes

Plan from 2000+ Industry-ready Training Programs

Experience Hands-On Learning from Industry Experts

Delivery Capability Across 100+ Countries & 10+ Languages

Skills Your Employees Will Gain

These are the core, hands-on capabilities your team builds during the program.

Model Performance Analysis
Model Performance Analysis involves evaluating the effectiveness of predictive models using metrics like accuracy and precision. This skill is important for data scientists and analysts to ensure models deliver reliable insights and drive informed decision-making.
Classification Model Construction
Classification Model Construction involves creating algorithms to categorize data into predefined classes. This skill is important for data scientists and machine learning engineers, as it enables accurate predictions and informed decision-making.
Web App Deployment
Web App Deployment is the process of launching web applications on servers for public access. This skill is important for developers and DevOps roles to ensure seamless user experiences and efficient updates.
Neural Network Implementation
Neural Network Implementation involves designing and deploying neural networks for tasks like classification and prediction. This skill is important for data scientists and AI engineers, as it enables them to develop advanced models that drive insights and innovation.
Debugging and Troubleshooting
Debugging And Troubleshooting involve identifying, diagnosing, and resolving issues in software or systems. this skill is important for developers and IT professionals to ensure smooth operations and enhance user experience.
Model Integration with Web Apps
Model Integration With Web Apps involves connecting machine learning models to web applications for real-time data processing. This skill is important for developers and data scientists to enhance user experiences and drive data-driven decision-making.

What Your Team Will Achieve After This Training

Analyze and interpret model performance metrics
Construct classification models for data categorization
Deploy machine learning web apps in real-world scenarios
Implement neural networks for complex data processing tasks
Debug and troubleshoot machine learning web apps effectively
Integrate machine learning models seamlessly into web applications
Apply Tensorflow.js to develop regression models for predictive analytics

Topics & Program Outline

The curriculum is organized into focused modules built by industry experts and delivered virtually or on-premise. Interactive sessions reflect the evolving demands of the workplace, keeping the learning both relevant and practical.

Getting Started with TensorFlow.js

Introduction to TensorFlow.js
- A high-level overview of TensorFlow.js and its capabilities
- Key benefits and applications of using TensorFlow.js
- Comparing TensorFlow.js with other machine learning libraries
Setting up the development environment
- Choosing a suitable code editor
- Installing TensorFlow.js using different methods
- Creating and configuring a basic web development project
Exploring TensorFlow.js features
- Tensors
- Variables
- Layers
- Optimizers
- Loss functions
- Data Preprocessing
- Model Visualization

TensorFlow.js Basics

Understanding tensors and operations
- Introduction to tensors
- Common tensor operations
- Broadcasting
Building and training simple models
- Creating sequential models
- Adding layers to the model
- Training the model
Evaluating model performance
- Common evaluation metrics
- Selecting appropriate metric
- Calculating and interpreting evaluation metrics

Regression

Linear regression with TensorFlow.js
- Implementing the linear regression model using TensorFlow.js layers
- Understanding the model's architecture and parameters
- Training the model with appropriate loss function and optimizer
- Evaluating the model's performance using metrics
Polynomial regression
- Transforming features
- Building and training a polynomial regression model in TensorFlow.js
- Comparing its performance
Time-series forecasting
- Understanding time series data and its characteristics
- Preprocessing time series data for forecasting
- Building models for time series forecasting
- Training and evaluating time series forecasting models in TensorFlow.js.

Neural Networks

Building feedforward neural networks
- Understanding the basic structure of feedforward neural networks.
- Creating different types of layers
- Connecting layers to form a neural network architecture.
Training neural networks
- Defining the training process
- Choosing appropriate optimizers
- Using training techniques
Optimizing neural network performance
- Understanding hyperparameter tuning
- Using validation sets
- Early stopping
- Techniques like data augmentation and regularization (L1/L2 regularization)

Classification

Binary classification
- Understanding binary classification problems
- Selecting suitable activation functions
- Training the model with appropriate loss functions
- Evaluating the model's performance using metrics
Multi-class classification
- Understanding problems with more than two classes
- Using one-hot encoding to represent multiple classes as vectors
- Selecting suitable activation functions
- Training the model with suitable loss functions and optimizers
- Evaluating the model's performance using appropriate metrics
Image classification with Convolutional Neural Networks (CNNs)
- Understanding the concept of convolutional layers and their benefits
- Building a CNN architecture for image classification
- Training the CNN with appropriate loss functions and optimizers
- Using transfer learning with pre-trained models
- Evaluating the model's performance using metrics

Who Should Attend?

This program suits professionals at many levels across the organization, including:

Data Scientists
Software Engineers
AI Developers
Machine Learning Engineers
Research Scientists
IT Professionals
Business Analysts
Systems Architects
Technical Leads
Data Engineers
Product Managers
Analytics Managers

What are the Prerequisites?

Professionals with a basic understanding of machine learning concepts and proficiency in JavaScript programming can take up the Tensorflow.js training course.

Request a Quote for your Corporate Training Requirements

Delivering Training for Organizations across 100 Countries and 10+ Languages

Choose the Format That Fits Your Team

We design training your teams actually engage with, and deliver it the way that suits you best. Through a vetted global trainer network, Edstellar runs sessions in 10+ languages with consistent quality anywhere.

Virtual / online: expert-led live sessions delivered anywhere, with consistency and easy scheduling.

We deliver anywhere worldwide

Standardized content for consistent outcomes

Join from own workspace, no travel

We scale to large groups across sites

Interactive tools keep remote learners engaged

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On-site (in-house): immersive, instructor-led learning at your office.

Our trainers run face-to-face at your office

We tailor setup/content to your workplace and tools

Group exercises drive collaboration

Live demos + hands-on practice

Direct trainer access to clarify doubts

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Off-site: focused, instructor-led group learning away from everyday workplace distractions.

We host your teams at a venue of your preferred choice

Built-in group activities for bonding

Full uninterrupted schedule for focus/retention

Boosts morale and signals commitment

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What Sets Edstellar Apart

Experienced Trainers

Our trainers are drawn from a vetted global network and bring years of industry expertise, keeping every session practical and impactful.

Proven Quality

With a strong global track record, Edstellar is known for quality and engaging delivery.

Industry-Relevant Curriculum

Our programs are built by experts to match the demands of today's industry.

Fully Customizable

Every program can be tailored to your organization's goals.

Comprehensive Support

We provide pre- and post-session support for a complete learning experience.

Global Multi-Location & Multilingual Training Delivery

We deliver in multiple languages to support diverse global teams.

Hear from Organizations We've Trained

"The Tensorflow.js training provided me with comprehensive capabilities that elevated my expertise. As a Web Developer, I needed to understand practical applications deeply, and this course delivered perfectly. The practical gave me hands-on experience with industry best practices. These specialized skills have positioned me for significant advancement opportunities within my organization. Highly recommend for anyone serious about this field.”

Sarah Hawkins

Web Developer,

Neural Network Solutions Firm

"This Tensorflow.js course equipped me with comprehensive advanced methodologies expertise that I've seamlessly integrated into our professional services practice. The hands-on modules covering hands-on exercises and real-world case solutions that consistently deliver measurable business results. Our solution delivery efficiency and quality have increased substantially across the board, validating the immediate impact of this training program.”

Daniel Leitner

Application Developer,

Machine Learning Framework Provider

"As a JavaScript Developer leading technical mastery operations, the Tensorflow.js training provided our team with essential strategic frameworks expertise at scale. The comprehensive modules on expert-led workshops and complete operational footprint. We reduced operational costs by 40% while simultaneously improving service quality standards. This course has proven invaluable for driving our organizational transformation and sustained excellence.”

Mahmud Qasim

JavaScript Developer,

Deep Learning Platform Provider

“Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

Aditi Rao

L&D Head,

A Global Technology Company

Recognition That Motivates Your Team

Upon successful completion of the training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

Corporate Tensorflow.js Training Course

Drive Team Excellence with Tensorflow.js Corporate Training

Skills Your Employees Will Gain

What Your Team Will Achieve After This Training

Topics & Program Outline

Getting Started with TensorFlow.js

TensorFlow.js Basics

Regression

Neural Networks

Classification

Who Should Attend?

What are the Prerequisites?

Choose the Format That Fits Your Team

Get a Proposal Shaped to Your Needs

What Sets Edstellar Apart

Experienced Trainers

Proven Quality

Industry-Relevant Curriculum

Fully Customizable

Comprehensive Support

Global Multi-Location & Multilingual Training Delivery

Hear from Organizations We've Trained

Recognition That Motivates Your Team

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