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Machine Learning Handbook
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Gain insights into ML fundamentals, explore Python libraries, and delve into real-world applications like Tesla and ChatGPT. Discover traditional vs. deep learning for data-driven decision-making.

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Overview

Content

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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 tasks and their applications in the real world, including Tesla self-driving cars, OpenAI, ChatGPT, and others. The course also provides insights into various ML types and a comparative analysis between traditional ML approaches and the latest advancements in deep learning. With the completion of this course, you’ll emerge with a concise yet comprehensive knowledge of machine learning. It will equip you with the required skills to enhance your machine learning knowledge for data-driven decision-making.

This course offers a thorough initiation into the field of machine learning (ML), a branch of artificial intelligence focussing ...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

Content

12 Lessons3 Quizzes

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

Fake News Detection Using Scikit-learn

Project

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

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Machine Learning Handbook Save

Machine Learning Handbook
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