Udemy

Python & TensorFlow: Deep Dive into Machine Learning

立即報名
  • 50,164 名學生
  • 更新於 2/2024
4.3
(269 個評分)
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課程資料

報名日期*
全年招生
課程級別
學習模式
修業期
3 小時 1 分鐘
教學語言
英語
授課導師
Meta Brains, Skool of AI
評分
4.3
(269 個評分)
*提示: 以上時間表僅供參考,以機構網站為準。

課程簡介

Python & TensorFlow: Deep Dive into Machine Learning

Python & TensorFlow: The Roadmap to Deep Machine Learning Expertise

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!


課程章節

  • 10 個章節
  • 36 堂課
  • 第 1 章 Introduction to Machine & Deep Learning
  • 第 2 章 Basics of TensorFlow & Installation
  • 第 3 章 Machine Learning Part 1 : Supervised Learning
  • 第 4 章 Machine Learning Part 2 : Unsupervised Learning
  • 第 5 章 Deep Learning Basics with Tensorflow : Neural Networks
  • 第 6 章 Model Evaluation & Optimization
  • 第 7 章 TensorFlow for Production
  • 第 8 章 Project: Image Classification
  • 第 9 章 Conclusion
  • 第 10 章 BONUS Section - Don't Miss Out

課程內容

  • 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

評價

  • P
    Prince Cyrus Sarpong
    4.0

    II love the simple explanation

  • L
    Letlhogonolo Letsapa
    5.0

    Very informative with well presented details.

  • R
    Rachel Tang Pei Yin
    4.5

    Good experience for learning

  • H
    Harshal Mahajan
    5.0

    got perfect knowledge about python

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