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Python & TensorFlow: Deep Dive into Machine Learning

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Python & TensorFlow: Deep Dive into Machine Learning, available at $19.99, has an average rating of 4.26, with 36 lectures, based on 127 reviews, and has 31794 subscribers.

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You will learn about Grasp fundamentals of machine learning, deep learning, and their applications Set up and navigate TensorFlow, understanding its architecture and APIs Master supervised learning algorithms such as linear regression, SVMs, and decision trees Dive into unsupervised techniques including clustering and PCA Understand and construct neural networks, including CNNs and RNNs, using TensorFlow Evaluate and optimize ML models, addressing overfitting and mastering hyperparameter tuning Deploy TensorFlow models in production environments Apply skills in a hands-on image classification project Transition from Python basics to advanced ML & TensorFlow applications This course is ideal for individuals who are Beginners in Data Science and AI: Individuals looking to kick-start their journey in machine learning and deep learning or Python Developers: Programmers familiar with Python seeking to expand their skill set into AI and TensorFlow applications or Data Analysts and Statisticians: Professionals looking to transition or incorporate machine learning techniques into their analysis workflows or Tech Enthusiasts: Those curious about the latest trends in AI and wanting to get hands-on with TensorFlow and Python or Students: Undergraduates or postgraduates studying computer science, data science, or a related field and wanting a comprehensive and practical overview or Career Changers: Professionals from other fields wanting to pivot into data science or AI roles or Researchers: Individuals in scientific or academic roles looking to understand or employ ML techniques in their work or Business Professionals: Managers or decision-makers wanting to understand the capabilities and limitations of machine learning and how it can impact their business or Freelancers: Developers or consultants looking to expand their service offerings by mastering machine learning tools and frameworks It is particularly useful for Beginners in Data Science and AI: Individuals looking to kick-start their journey in machine learning and deep learning or Python Developers: Programmers familiar with Python seeking to expand their skill set into AI and TensorFlow applications or Data Analysts and Statisticians: Professionals looking to transition or incorporate machine learning techniques into their analysis workflows or Tech Enthusiasts: Those curious about the latest trends in AI and wanting to get hands-on with TensorFlow and Python or Students: Undergraduates or postgraduates studying computer science, data science, or a related field and wanting a comprehensive and practical overview or Career Changers: Professionals from other fields wanting to pivot into data science or AI roles or Researchers: Individuals in scientific or academic roles looking to understand or employ ML techniques in their work or Business Professionals: Managers or decision-makers wanting to understand the capabilities and limitations of machine learning and how it can impact their business or Freelancers: Developers or consultants looking to expand their service offerings by mastering machine learning tools and frameworks.

Enroll now: Python & TensorFlow: Deep Dive into Machine Learning

Summary

Title: Python & TensorFlow: Deep Dive into Machine Learning

Price: $19.99

Average Rating: 4.26

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: $69.99

Quality Status: approved

Status: Live

What You Will Learn

  • Grasp fundamentals of machine learning, deep learning, and their applications
  • Set up and navigate TensorFlow, understanding its architecture and APIs
  • Master supervised learning algorithms such as linear regression, SVMs, and decision trees
  • Dive into unsupervised techniques including clustering and PCA
  • Understand and construct neural networks, including CNNs and RNNs, using TensorFlow
  • Evaluate and optimize ML models, addressing overfitting and mastering hyperparameter tuning
  • Deploy TensorFlow models in production environments
  • Apply skills in a hands-on image classification project
  • Transition from Python basics to advanced ML & TensorFlow applications

Who Should Attend

  • Beginners in Data Science and AI: Individuals looking to kick-start their journey in machine learning and deep learning
  • Python Developers: Programmers familiar with Python seeking to expand their skill set into AI and TensorFlow applications
  • Data Analysts and Statisticians: Professionals looking to transition or incorporate machine learning techniques into their analysis workflows
  • Tech Enthusiasts: Those curious about the latest trends in AI and wanting to get hands-on with TensorFlow and Python
  • Students: Undergraduates or postgraduates studying computer science, data science, or a related field and wanting a comprehensive and practical overview
  • Career Changers: Professionals from other fields wanting to pivot into data science or AI roles
  • Researchers: Individuals in scientific or academic roles looking to understand or employ ML techniques in their work
  • Business Professionals: Managers or decision-makers wanting to understand the capabilities and limitations of machine learning and how it can impact their business
  • Freelancers: Developers or consultants looking to expand their service offerings by mastering machine learning tools and frameworks

Target Audiences

  • Beginners in Data Science and AI: Individuals looking to kick-start their journey in machine learning and deep learning
  • Python Developers: Programmers familiar with Python seeking to expand their skill set into AI and TensorFlow applications
  • Data Analysts and Statisticians: Professionals looking to transition or incorporate machine learning techniques into their analysis workflows
  • Tech Enthusiasts: Those curious about the latest trends in AI and wanting to get hands-on with TensorFlow and Python
  • Students: Undergraduates or postgraduates studying computer science, data science, or a related field and wanting a comprehensive and practical overview
  • Career Changers: Professionals from other fields wanting to pivot into data science or AI roles
  • Researchers: Individuals in scientific or academic roles looking to understand or employ ML techniques in their work
  • Business Professionals: Managers or decision-makers wanting to understand the capabilities and limitations of machine learning and how it can impact their business
  • Freelancers: Developers or consultants looking to expand their service offerings by mastering machine learning tools and frameworks

Welcome to our Python & TensorFlow for Machine Learning complete course. This intensive program is designed for both beginners eager to dive into the world of data science and seasoned professionals looking to deepen their understanding of machine learning, deep learning, and TensorFlow’s capabilities.

Starting with Python—a cornerstone of modern AI development—we’ll guide you through its essential features and libraries that make data manipulation and analysis a breeze. As we delve into machine learning, you’ll learn the foundational algorithms and techniques, moving seamlessly from supervised to unsupervised learning, paving the way for the magic of deep learning.

With TensorFlow, one of the most dynamic and widely-used deep learning frameworks, we’ll uncover how to craft sophisticated neural network architectures, optimize models, and deploy AI-powered solutions. We don’t just want you to learn—we aim for you to master. By the course’s end, you’ll not only grasp the theories but also gain hands-on experience, ensuring that you’re industry-ready.

Whether you aspire to innovate in AI research or implement solutions in business settings, this comprehensive course promises a profound understanding, equipping you with the tools and knowledge to harness the power of Python, Machine Learning, and TensorFlow.

We’re excited about this journey, and we hope to see you inside!

Course Curriculum

Chapter 1: Introduction to Machine & Deep Learning

Lecture 1: What is Machine Learning?

Lecture 2: Types of Machine Learning

Lecture 3: Applications of Machine Learning

Lecture 4: What is Deep Learning?

Lecture 5: Course Materials

Chapter 2: Basics of TensorFlow & Installation

Lecture 1: What is TensorFlow?

Lecture 2: Installing and Setting up TensorFlow

Lecture 3: TensorFlow Architecture

Lecture 4: A refresher on APIs

Lecture 5: TensorFlow APls

Chapter 3: Machine Learning Part 1 : Supervised Learning

Lecture 1: What is Supervised Learning?

Lecture 2: Linear Regression

Lecture 3: Logistic Regression

Lecture 4: Decision Trees

Lecture 5: Random Forests

Lecture 6: Support Vector Machines (SVMs)

Chapter 4: Machine Learning Part 2 : Unsupervised Learning

Lecture 1: What is Unsupervised Learning?

Lecture 2: K-Means Clustering

Lecture 3: Hierarchical Clustering

Lecture 4: Principal Component Analysis (PCA)

Chapter 5: Deep Learning Basics with Tensorflow : Neural Networks

Lecture 1: What are Neural Networks?

Lecture 2: Basic Neural Networks

Lecture 3: Convolutional Neural Networks (CNNs)

Lecture 4: Recurrent Neural Networks (RNNs)

Lecture 5: Building Deep Neural Networks

Chapter 6: Model Evaluation & Optimization

Lecture 1: Training and Testing Data

Lecture 2: Model Evaluation Metrics

Lecture 3: Overfitting and Underfitting

Lecture 4: Hyperparameter Tuning

Chapter 7: TensorFlow for Production

Lecture 1: Saving and restoring models

Lecture 2: Deploying TensorFlow models

Lecture 3: Distributed TensorFlow

Lecture 4: TensorBoard for visualization and debugging

Chapter 8: Project: Image Classification

Lecture 1: ML Project : Image classification Model

Chapter 9: Conclusion

Lecture 1: Conclusion

Chapter 10: BONUS Section – Don't Miss Out

Lecture 1: BONUS Section – Don't Miss Out

Instructors

Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 7 votes
  • 3 stars: 20 votes
  • 4 stars: 43 votes
  • 5 stars: 57 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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