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Python & TensorFlow: The Roadmap to Deep Machine Learning Expertise

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

Description

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 Pythonโ€”a cornerstone of modern AI developmentโ€”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 learnโ€”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.


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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!

English
language

Content

Introduction to Machine & Deep Learning

What is Machine Learning?
Types of Machine Learning
Applications of Machine Learning
What is Deep Learning?

Basics of TensorFlow & Installation

What is TensorFlow?
Installing and Setting up TensorFlow
TensorFlow Architecture
A refresher on APIs
TensorFlow APls

Machine Learning Part 1 : Supervised Learning

What is Supervised Learning?
Linear Regression
Logistic Regression
Decision Trees
Random Forests
Support Vector Machines (SVMs)

Machine Learning Part 2 : Unsupervised Learning

What is Unsupervised Learning?
K-Means Clustering
Hierarchical Clustering
Principal Component Analysis (PCA)

Deep Learning Basics with Tensorflow : Neural Networks

What are Neural Networks?
Basic Neural Networks
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Building Deep Neural Networks

Model Evaluation & Optimization

Training and Testing Data
Model Evaluation Metrics
Overfitting and Underfitting
Hyperparameter Tuning

TensorFlow for Production

Saving and restoring models
Deploying TensorFlow models
Distributed TensorFlow
TensorBoard for visualization and debugging

Project: Image Classification

ML Project : Image classification Model

Conclusion

Conclusion