Corporate Deep Learning with TensorFlow Training Course

Name: Deep Learning with TensorFlow Training
Availability: InStock

Edstellar’s Deep Learning with TensorFlow instructor-led training course equips professionals with advanced skills in AI and machine learning. The course covers the fundamentals of TensorFlow, activation functions, and deep learning techniques. Upskill your team to gain proficiency in deep learning techniques using TensorFlow.

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 Deep Learning with TensorFlow Corporate Training

Deep Learning with TensorFlow is the application of deep learning techniques using the TensorFlow framework, an open-source library developed by Google for building and deploying machine learning models. The course helps professionals by enabling them to leverage advanced artificial intelligence techniques to analyze vast amounts of data, uncover valuable insights, and innovate across various domains. Deep Learning with TensorFlow training empowers professionals to develop innovative solutions, optimize processes, and drive teams growth.

Edstellar's virtual/onsite Deep Learning with TensorFlow training course provides customization and employs cutting-edge methodologies. Our trainers are highly regarded for their expertise in delivering the Deep Learning with TensorFlow instructor-led training course and possess vast experience in navigating the intricacies of the framework for building and deploying neural networks, optimizing models, and interpreting results.

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

Deep Learning with TensorFlow skills corporate training will enable teams to effectively apply their learnings at work.

TensorFlow Documentation Analysis
TensorFlow Documentation Analysis involves interpreting and understanding TensorFlow's documentation to effectively implement machine learning models. This skill is important for data scientists and ML engineers, as it ensures accurate model development and troubleshooting.
Neural Network Architecture Design
Neural Network Architecture Design involves creating optimal structures for neural networks to solve specific problems. This skill is important for AI developers and data scientists, as it enhances model performance and efficiency in tasks like image recognition and natural language processing.
Practical Implementation with TensorFlow
Practical Implementation With TensorFlow involves applying TensorFlow to build, train, and deploy machine learning models. This skill is important for data scientists and AI engineers, as it enables them to create effective solutions for real-world problems.
Hyperparameter and Parameter Optimization
Hyperparameter and Parameter Optimization involves fine-tuning model settings to enhance performance. This skill is important for data scientists and machine learning engineers to ensure accurate, efficient models.
Deep Learning Experimentation
Deep Learning Experimentation involves designing, testing, and refining neural network models. This skill is important for data scientists and AI engineers to optimize performance and innovate solutions.
Transfer Learning
Transfer Learning is a machine learning technique where knowledge gained from one task is applied to a different but related task. This skill is important for data scientists and AI engineers as it enhances model efficiency, reduces training time, and improves performance on limited data.

What Your Team Will Achieve After This Training

Analyze TensorFlow documentation and resources to implement deep learning algorithms
Design customized neural network architectures tailored to specific problem domains
Implement theoretical knowledge into practical solutions using TensorFlow
Optimize hyperparameters and model parameters to enhance performance
Troubleshoot and resolve common issues encountered during model training and evaluation
Modify pre-trained models for transfer learning and domain-specific applications
Experiment with various deep learning techniques and frameworks to innovate solutions

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.

Introduction to TensorFlow

Overview of TensorFlow and its ecosystem
- History and development of TensorFlow
- Key features and functionalities
- Comparison with other deep learning frameworks
- TensorFlow ecosystem
Installation and setup
- Different installation methods
- Setting up virtual environments
- GPU and TPU support
Basics of tensor operations
- Understanding tensors
- Creating and manipulating tensors
- Common tensor operations
- Introduction to data types and shapes

Artificial Neural Networks

Fundamentals of neural networks
- Biological inspiration and analogy
- Perceptrons: the building block of neural networks
- Activation functions and their role
- Learning and training process
Building a simple neural network in TensorFlow
- Defining the network architecture
- Implementing forward pass and backpropagation
- Training the network on a dataset
Understanding layers and neurons
- Different types of layers
- Activation functions specific to different layers
- Hyperparameters and their impact on network performance

Activation Functions

Role of activation functions in neural networks
- Introducing non-linearity into the network
- Mapping input values to output values
- Choosing appropriate functions for different scenarios
Popular activation functions
- Sigmoid function and its limitations
- ReLU (Rectified Linear Unit) and its variations
- Tanh function and its properties
- Softmax function for multi-class classification
Selecting appropriate activation functions for different tasks
- Choosing based on data distribution and task type
- Understanding the impact of different activations

Deep Learning Techniques

Convolutional neural networks (CNNs) for image recognition
- Convolutional layers and pooling operations
- Architectures for image classification
- Applications in object
Recurrent neural networks (RNNs) for sequence modeling
- Understanding sequence data and its challenges
- Vanilla RNNs, LSTMs, and GRUs
- Applications in machine translation, text generation, etc.
Generative Adversarial Networks (GANs) for generating synthetic data
- Generative model and discriminative model in a GAN
- Training process and challenges
- Applications in image generation

Deep Learning Applications

Image classification and object detection
- Preprocessing and preparing image data
- Training and evaluating models for different tasks
- Real-world applications
Natural Language Processing (NLP) tasks such as sentiment analysis and text generation
- Text preprocessing and tokenization
- Word embeddings and language models
- Applications in sentiment analysis
Recommendation systems using collaborative filtering:
- Matrix factorization and user-item interactions
- Building recommender systems
- Applications in e-commerce

Computing Gradients

Understanding gradients and their role in optimization
- The concept of gradients and their calculation
- Relating gradients to learning and weight updates
- Visualization of gradients
Automatic differentiation in TensorFlow
- TensorFlow's built-in functionality for calculating gradients
- Simplifying the process of backpropagation
- Using tf.GradientTape for efficient gradient calculation
Gradient descent optimization algorithms
- Stochastic Gradient Descent (SGD) and its variants
- Tuning learning rate and other hyperparameters
- Monitoring loss function and optimizing for convergence

Single-Layer and Multi-Layer Perceptron

Building and training single-layer perceptrons
- Implementing logic gates (AND, OR, etc.) using perceptrons
- Training on simple datasets and visualizing results
- Limitations of single-layer perceptrons
Extending to Multi-Layer Perceptrons (MLPs) for more complex tasks
- Adding hidden layers and increasing network capacity
- Understanding the backpropagation process in MLPs
- Training MLPs on more complex datasets
Practical applications and case studies
- Using MLPs for image classification
- Real-world examples and case studies

Who Should Attend?

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

Deep Learning Engineers
Data Scientists
Product Managers
Machine Learning Engineers
Research Scientists
Software Developers
AI Researchers
Computer Vision Engineers
NLP Engineers
Data Engineers
Predictive Modelers
Robotics Engineers

What Are the Prerequisites?

Professionals with a basic understanding of the Python programming language can take up the Deep Learning with TensorFlow 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 Deep Learning with TensorFlow Training

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

Enquire now

On-site Deep Learning with TensorFlow Training

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 Deep Learning with TensorFlow Training

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

Enquire now

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

"Attending the Deep Learning with TensorFlow training was transformational for my professional development. As a Principal Learning Analytics Manager, the deep dive into industry best practices gave me the confidence to of expert-led workshops were immediately applicable to my work. The knowledge gained has been immediately applicable to mission-critical projects and initiatives. This course has become foundational to my continued success.”

Marcus Dixon

Principal Learning Analytics Manager,

Machine Learning Framework Provider

"This Deep Learning with TensorFlow course transformed my approach to professional expertise solutions. The comprehensive modules on real-world case studies were invaluable for our strategic projects. I can now confidently methodologies for diverse client requirements. The deep coverage of hands-on exercises gave me advanced skills I immediately applied to We've successfully expanded our service portfolio based on these enhanced capabilities.”

Huang Lan

Lead Training Technology Manager,

AI Model Development Company

"As a Principal Instructional Designer leading technical mastery operations, the Deep Learning with TensorFlow training provided our team with essential strategic frameworks expertise at scale. The comprehensive modules across our complete operational footprint. Our stakeholder satisfaction and NPS scores reached unprecedented all-time highs. This course has proven invaluable for driving our organizational transformation and sustained excellence.”

Maher Yaser

Principal Instructional Designer,

Neural Network Solutions Firm

“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 Deep Learning with TensorFlow Training Course

Drive Team Excellence with Deep Learning with TensorFlow Corporate Training

Skills Your Employees Will Gain

What Your Team Will Achieve After This Training

Topics & Program Outline

Introduction to TensorFlow

Artificial Neural Networks

Activation Functions

Deep Learning Techniques

Deep Learning Applications

Computing Gradients

Single-Layer and Multi-Layer Perceptron

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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