From Zero to AI Hero: Create Neural Networks with TensorFlow
From Zero to AI Hero: Create Neural Networks with TensorFlow, available at $64.99, has an average rating of 4.1, with 64 lectures, based on 11 reviews, and has 40 subscribers.
You will learn about Understand the fundamentals of artificial intelligence and machine learning. Set up the TensorFlow environment to begin building neural networks. Explore the reasons behind learning TensorFlow and its importance in the field of machine learning. Gain familiarity with AI and machine learning concepts, including supervised learning, unsupervised learning, and neural networks. Apply the machine learning workflow using TensorFlow and Python, from data preprocessing to model evaluation. Comprehend the inner workings of neural networks, including their architecture, activation functions, and backpropagation algorithm. Build and train their first neural network using TensorFlow, implementing various layers, optimization techniques, and loss functions. Monitor and improve the performance of neural networks through techniques such as regularization and hyperparameter tuning. Learn techniques for deploying trained neural networks, including model conversion and deployment options. Receive practical tips and best practices for working with TensorFlow and neural networks. Gain hands-on experience through coding exercises and projects, allowing students to apply their knowledge and build their own neural network models. Obtain a comprehensive understanding of the entire process of building, training, and deploying neural networks with TensorFlow. Acquire the confidence to continue exploring and experimenting with neural networks for various real-world applications. This course is ideal for individuals who are Anyone with a curiosity for machine learning and a desire to build intelligent systems using TensorFlow. or Entrepreneurs or business professionals interested in understanding the capabilities and potential applications of artificial intelligence in their industry. or Professionals in fields such as finance, healthcare, or marketing, who want to leverage the power of neural networks for data analysis and decision-making. or Students pursuing computer science or related fields who want to explore the exciting world of machine learning. or Technology enthusiasts who want to understand the fundamentals of artificial intelligence and how neural networks work. or Software developers interested in expanding their knowledge and incorporating machine learning into their applications. or Aspiring data scientists looking to enhance their skills in deep learning and neural networks. It is particularly useful for Anyone with a curiosity for machine learning and a desire to build intelligent systems using TensorFlow. or Entrepreneurs or business professionals interested in understanding the capabilities and potential applications of artificial intelligence in their industry. or Professionals in fields such as finance, healthcare, or marketing, who want to leverage the power of neural networks for data analysis and decision-making. or Students pursuing computer science or related fields who want to explore the exciting world of machine learning. or Technology enthusiasts who want to understand the fundamentals of artificial intelligence and how neural networks work. or Software developers interested in expanding their knowledge and incorporating machine learning into their applications. or Aspiring data scientists looking to enhance their skills in deep learning and neural networks.
Enroll now: From Zero to AI Hero: Create Neural Networks with TensorFlow
Summary
Title: From Zero to AI Hero: Create Neural Networks with TensorFlow
Price: $64.99
Average Rating: 4.1
Number of Lectures: 64
Number of Published Lectures: 64
Number of Curriculum Items: 64
Number of Published Curriculum Objects: 64
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand the fundamentals of artificial intelligence and machine learning.
- Set up the TensorFlow environment to begin building neural networks.
- Explore the reasons behind learning TensorFlow and its importance in the field of machine learning.
- Gain familiarity with AI and machine learning concepts, including supervised learning, unsupervised learning, and neural networks.
- Apply the machine learning workflow using TensorFlow and Python, from data preprocessing to model evaluation.
- Comprehend the inner workings of neural networks, including their architecture, activation functions, and backpropagation algorithm.
- Build and train their first neural network using TensorFlow, implementing various layers, optimization techniques, and loss functions.
- Monitor and improve the performance of neural networks through techniques such as regularization and hyperparameter tuning.
- Learn techniques for deploying trained neural networks, including model conversion and deployment options.
- Receive practical tips and best practices for working with TensorFlow and neural networks.
- Gain hands-on experience through coding exercises and projects, allowing students to apply their knowledge and build their own neural network models.
- Obtain a comprehensive understanding of the entire process of building, training, and deploying neural networks with TensorFlow.
- Acquire the confidence to continue exploring and experimenting with neural networks for various real-world applications.
Who Should Attend
- Anyone with a curiosity for machine learning and a desire to build intelligent systems using TensorFlow.
- Entrepreneurs or business professionals interested in understanding the capabilities and potential applications of artificial intelligence in their industry.
- Professionals in fields such as finance, healthcare, or marketing, who want to leverage the power of neural networks for data analysis and decision-making.
- Students pursuing computer science or related fields who want to explore the exciting world of machine learning.
- Technology enthusiasts who want to understand the fundamentals of artificial intelligence and how neural networks work.
- Software developers interested in expanding their knowledge and incorporating machine learning into their applications.
- Aspiring data scientists looking to enhance their skills in deep learning and neural networks.
Target Audiences
- Anyone with a curiosity for machine learning and a desire to build intelligent systems using TensorFlow.
- Entrepreneurs or business professionals interested in understanding the capabilities and potential applications of artificial intelligence in their industry.
- Professionals in fields such as finance, healthcare, or marketing, who want to leverage the power of neural networks for data analysis and decision-making.
- Students pursuing computer science or related fields who want to explore the exciting world of machine learning.
- Technology enthusiasts who want to understand the fundamentals of artificial intelligence and how neural networks work.
- Software developers interested in expanding their knowledge and incorporating machine learning into their applications.
- Aspiring data scientists looking to enhance their skills in deep learning and neural networks.
Get ready to build, train, and deploy intelligent systems that can revolutionize various industries and solve complex problems.
Are you fascinated by the world of artificial intelligence and machine learning?
Do you want to unlock the power of neural networks and learn how to build intelligent systems?
Look no further!Join our comprehensive course on building, training, and deploying neural networks with TensorFlow, the leading framework for deep learning in Python.
In this course, you will embark on an exciting journey that will take you from the fundamentals of TensorFlow to creating your very own neural networks. Whether you are a beginner in machine learning or an experienced developer looking to expand your skillset, this course is designed to cater to learners of all levels. No prior knowledge of TensorFlow or deep learning is required!
Why choose this course?
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Practical approach: We believe in hands-on learning, and this course is packed with real-world examples and projects that will reinforce your understanding of TensorFlow and neural networks.
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User-friendly structure:Our course is organized into ten engaging lessons, allowing you to progress step-by-step at your own pace. Each lesson builds upon the previous one, ensuring a seamless learning experience.
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Python-powered: Python is the language of choice for machine learning, and this course leverages its simplicity and versatility to teach you the concepts and techniques required to build powerful neural networks.
What will you learn in comprehensive and user-friendly course?
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Course Overview: Get acquainted with the course structure and objectives, setting the stage for your deep learning journey.
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Why Learn TensorFlow: Discover the significance of TensorFlow in the world of AI and machine learning, and learn why it’s the go-to framework for neural networks.
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Setting up the TensorFlow Environment:Learn how to install and configure TensorFlow on your machine, ensuring a smooth development experience.
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AI and Machine Learning Concepts: Build a strong foundation by exploring essential concepts in artificial intelligence and machine learning.
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Applying the Machine Learning Workflow with TensorFlow and Python: Understand the end-to-end process of building machine learning models using TensorFlow and Python, from data preparation to model evaluation.
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Understanding Neural Networks: Dive deep into the world of neural networks, understanding their structure, components, and functioning.
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Building and Training Your First Neural Network: Roll up your sleeves and start building! Learn how to design and train your very own neural network using TensorFlow.
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Monitoring and Improving Neural Network Performance:Discover techniques to monitor and evaluate the performance of your neural network, and explore strategies to enhance its accuracy and efficiency.
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Deploying Your Neural Network: Learn how to deploy your trained neural network into production environments, making it available for real-world applications.
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Final Words:Wrap up the course with a recap of the key concepts and insights gained, and explore avenues for further exploration and growth in the field of deep learning.
Example Projects:
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House Price Prediction:Harness the power of neural networks to predict house prices based on their sizes, gaining insights into regression tasks.
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Cloth Type Identification: Develop a neural network that can identify different types of clothing items from images, opening doors to image classification techniques.
Don’t miss this golden opportunity to unlock the power of artificial intelligence and machine learning.
Enroll now and take your first step towards becoming a TensorFlow hero!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Course Overview
Lecture 2: Project Files & Source Code
Lecture 3: Important Note About Video Playback Controls
Chapter 2: Why learn TenserFlow
Lecture 1: What Is TensorFlow
Lecture 2: Why TensorFlow
Lecture 3: TensorFlow Tools and Languages
Lecture 4: Required Skills
Lecture 5: Course Structure
Chapter 3: Setting up the TensorFlow Environment
Lecture 1: TensorFlow Development Environment
Lecture 2: What Is Google Colaboratory (aka Colab)
Lecture 3: Getting Started with Colab
Lecture 4: Importing TensorFlow
Lecture 5: Sequencing Code Execution
Lecture 6: Checklist and Summary
Chapter 4: AI and Machine Learning Concepts
Lecture 1: The Relationship of AI to ML (Artificial Intelligence and Machine Learning)
Lecture 2: Implementing Machine Learning
Lecture 3: Creating the Model
Lecture 4: Training the Model
Lecture 5: Reducing Loss
Lecture 6: Evaluating the Trained Model
Lecture 7: What Is a Tensor
Lecture 8: Checklist and Summary
Chapter 5: Applying the Machine Learning Workflow with TensorFlow
Lecture 1: Setting up the First Example Project (House Price Prediction)
Lecture 2: Defining the Problem and Getting Data
Lecture 3: Exploring the Data
Lecture 4: Preparing the Data
Lecture 5: Creating the Model
Lecture 6: Training the Model
Lecture 7: Improving Performance
Lecture 8: Evaluating Model Performance
Lecture 9: Summary
Chapter 6: Understanding Neural Networks
Lecture 1: Machine Learning with Neural Networks
Lecture 2: How Neurons Work
Lecture 3: Neuron Architecture
Lecture 4: Activation Functions
Lecture 5: From Neurons to Neural Networks
Lecture 6: Predicting with an Untrained Neural Network
Lecture 7: Training a Neural Network
Lecture 8: Summary
Chapter 7: Building and Training Your First Neural Network
Lecture 1: Building a Neural Network in TensorFlow (Image Classification Project)
Lecture 2: Getting and Preparing the Data
Lecture 3: Demonstration on Creating the Model
Lecture 4: Creating the Actual Real Model
Lecture 5: Compiling the Model
Lecture 6: Training and Evaluating the Model
Lecture 7: Summary
Chapter 8: Monitoring and Improving Neural Network Performance
Lecture 1: Understanding the Problem with Your Model
Lecture 2: TensorBoard Setup
Lecture 3: Monitoring Your Trained Model’s Performance
Lecture 4: Reducing Training Data Overfitting
Lecture 5: Randomly Dropping out Neuron Output
Lecture 6: Early Stopping
Lecture 7: Saving Your Trained Model
Lecture 8: Summary
Chapter 9: Deploying Your Neural Network
Lecture 1: What Is Deploying a Neural Network
Lecture 2: Installing TensorFlow ModelServer
Lecture 3: Understanding TensorFlow Model Serving
Lecture 4: Using TensorFlow Model Serving
Lecture 5: Summary
Chapter 10: Assignment
Lecture 1: Assignment Project
Chapter 11: Conclusion and Final Words
Lecture 1: What Have You Seen
Lecture 2: Training the Model
Lecture 3: Monitoring, Improving, and Deploying the Model
Lecture 4: Tips for Your Machine Learning Journey
Instructors
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Anass Cherkaoui
3D Artist, Graphic Designer as well as a Developer
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 1 votes
- 3 stars: 0 votes
- 4 stars: 3 votes
- 5 stars: 6 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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