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Machine Learning Handbook

This course is a hands-on intro to machine learning concepts anbd showcases the use of Python and its key ML libraries in practical coding examples.

Beginner

12 Lessons

2h 30min

Certificate of Completion

This course is a hands-on intro to machine learning concepts anbd showcases the use of Python and its key ML libraries in practical coding examples.

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Explanations

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Explanations

This course includes

5 Playgrounds

Course Overview

What You'll Learn

Course Content

Recommendations

Course Overview

This course offers a thorough initiation into the field of machine learning (ML), a branch of artificial intelligence focussing on creating and analyzing statistical algorithms capable of generalizing and executing tasks autonomously, without requiring explicit programming instructions. The course encompasses fundamental concepts showcasing the use of Python and its key libraries in practical coding examples. It delves into crucial areas, including an exploration of common libraries and tools used in ML t...Show More

What You'll Learn

An understanding of the fundamentals of machine learning (ML) in data-driven decision-making processes

Familiarity with essential libraries and tools used for data preprocessing

Knowledge of practical applications of ML in image processing, computer vision, text analysis, and natural language processing (NLP)

Proficiency in distinguishing between different types of ML approaches

An understanding of the distinctions between ML methodologies and its advanced concepts

An understanding of the fundamentals of machine learning (ML) in data-driven decision-making processes

Course Content

Introduction to Machine Learning

3 Lessons

Get familiar with key machine learning concepts, its significance in industries, and data-driven decision-making.

Course Overview

Overview of Machine Learning

Machine Learning’s Significance in Data-Driven Decisions

Common Libraries and Tools for Machine Learning Tasks

2 Lessons

Look at Python libraries and tools crucial for preprocessing and developing ML models.

Libraries for Machine Learning

Tools for Data Preprocessing and Model Development

Types of Machine Learning

4 Lessons

Master the steps to explore supervised, unsupervised, and reinforcement learning, and compare traditional machine learning with deep learning.

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Traditional Machine Learning vs. Deep Learning

Applications of Machine Learning

2 Lessons

Grasp the fundamentals of machine learning applications like image processing, computer vision, and NLP.

Image Processing and Computer Vision

Natural Language Processing (NLP)

The Way Forward

1 Lessons

Take a look at the essentials of machine learning, from basics to advanced applications.

Conclusion

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