Python Tensorflow Programming With Coding Exercises

Master Deep Learning with TensorFlow through Practical Coding Exercises

What you'll learn

How to build and train neural networks using TensorFlow.

Techniques for implementing CNNs and RNNs for specific tasks.

Methods for fine-tuning and optimizing deep learning models.

Practical skills in deploying TensorFlow models in real-world applications.

Requirements

Basic understanding of Python programming.

Familiarity with fundamental machine learning concepts.

Description

Welcome to Python TensorFlow Practices with Coding Exercises, a course designed to guide you through the essential concepts and techniques needed to excel in deep learning using TensorFlow. TensorFlow is one of the most powerful and widely used libraries for building machine learning and deep learning models. This course is crafted to help you gain hands-on experience in developing, training, and deploying neural networks with TensorFlow, providing you with the skills required to tackle real-world challenges in AI and data science.Why is learning TensorFlow necessary? As the demand for AI and machine learning continues to rise, the ability to build and implement deep learning models is becoming increasingly valuable. TensorFlow, developed by Google, is the go-to tool for professionals aiming to create scalable and efficient machine learning models. Whether you are an aspiring data scientist, a software engineer looking to specialize in AI, or a researcher aiming to incorporate deep learning into your work, this course is designed to meet your needs.Throughout the course, you will engage in coding exercises that cover a variety of topics, including:Introduction to TensorFlow and its ecosystemBuilding basic neural networks with TensorFlowImplementing convolutional neural networks (CNNs) for image recognitionDeveloping recurrent neural networks (RNNs) for sequence predictionTraining models using TensorFlow's Keras APIFine-tuning and optimizing models for better performanceDeploying TensorFlow models in production environmentsEach exercise is carefully structured to reinforce your understanding of TensorFlow and deep learning, ensuring that you can confidently apply these skills in practical scenarios.Instructor Introduction: Your instructor, Faisal Zamir, is a seasoned Python developer with over 7 years of teaching experience. Faisal’s deep expertise in Python programming and machine learning, combined with his practical teaching approach, will guide you through the complexities of TensorFlow with ease.30 Days Money-Back Guarantee: We believe in the effectiveness of our course, which is why we offer a 30-day money-back guarantee. If you're not completely satisfied, you can request a full refund, no questions asked.Certificate at the End of the Course: Upon completing the course, you will receive a certificate that recognizes your proficiency in TensorFlow and deep learning, making it a valuable addition to your professional portfolio.

Overview

Section 1: Introduction to TensorFlow

Lecture 1 Introduction to TensorFlow

Lecture 2 Lesson 01

Lecture 3 Coding Exercises with Solutions

Section 2: TensorFlow Core Concept

Lecture 4 TensorFlow Core Concept

Lecture 5 Lesson 02

Lecture 6 Coding Exercises with Solutions

Section 3: Linear Regression with TensorFlow

Lecture 7 Linear Regression with TensorFlow

Lecture 8 Lesson 03

Lecture 9 Coding Exercises with Solutions

Section 4: Classification with TensorFlow

Lecture 10 Classification with TensorFlow

Lecture 11 Lesson 04

Lecture 12 Coding Exercises with Solutions

Section 5: Neural Networks and TensorFlow

Lecture 13 Neural Networks and TensorFlow

Lecture 14 Lesson 05

Lecture 15 Coding Exercises with Solutions

Section 6: Convolutional Neural Networks (CNNs)

Lecture 16 Convolutional Neural Networks (CNNs)

Lecture 17 Lesson 06

Lecture 18 Coding Exercises with Solutions

Section 7: Recurrent Neural Networks (RNNs)

Lecture 19 Recurrent Neural Networks (RNNs)

Lecture 20 Lesson 07

Lecture 21 Coding Exercises with Solutions

Section 8: Transfer Learning with TensorFlow

Lecture 22 Transfer Learning with TensorFlow

Lecture 23 Lesson 08

Lecture 24 Coding Exercises with Solutions

Section 9: TensorFlow with Keras API

Lecture 25 TensorFlow with Keras API

Lecture 26 Lesson 09

Lecture 27 Coding Exercises with Solutions

Section 10: Deploying TensorFlow Models

Lecture 28 Deploying TensorFlow Models

Lecture 29 Lesson 10

Lecture 30 Coding Exercises with Solutions

Aspiring data scientists and AI professionals who want to specialize in deep learning.,Python developers looking to enhance their skills with TensorFlow.,Researchers and professionals aiming to integrate deep learning into their work.