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Machine Learning Handbook - Free AI-Powered Course
4.3
Beginner
2h 30min
Updated 2 months ago
Machine Learning Handbook
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
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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
Show more
Content
12 Lessons3 Quizzes
1.
Introduction to Machine Learning
3 Lessons
Get familiar with key machine learning concepts, its significance in industries, and data-driven decision-making.
2.
Common Libraries and Tools for Machine Learning Tasks
2 Lessons
Look at Python libraries and tools crucial for preprocessing and developing ML models.
3.
Types of Machine Learning
4 Lessons
Master the steps to explore supervised, unsupervised, and reinforcement learning, and compare traditional machine learning with deep learning.
4.
Applications of Machine Learning
2 Lessons
Grasp the fundamentals of machine learning applications like image processing, computer vision, and NLP.
5.
The Way Forward
1 Lessons
Take a look at the essentials of machine learning, from basics to advanced applications.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
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