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About Learn Machine Learning PRO

This app has been prepared for professionals aspiring to learn the complete picture of machine learning and artificial intelligence. This tutorial caters the learning needs of both the novice learners and experts, to help them understand the concepts and implementation of artificial intelligence and machine learning.

Who this machine learning course is for:
Anyone interested in Machine Learning. Students who have at least high school knowledge in math and who want to start learn Machine Learning.

Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.

Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.

- Any students in college who want to start a career in Data Science.
- Any data analysts who want to level up in Machine Learning.
- Any people who are not satisfied with their job and who want to become a Data Scientist.
- Any people who want to create added value to their business by using powerful Machine Learning tools.

In this App You Will Learn
- Why Choose Python for Machine Learning
- Machine Learning Roadmap
- Learn Python 3 for Machine Learning
- Learn Artificial Intelligence
- Introduction to Machine Learning
- Learn TensorFlow for machine learning
- Learn Pytorch guide
- Artificial Intelligence complete guide
- Learn Deep Learning
- Learn Machine Learning Complete Guide
- Machine Learning Projects and Examples
- Python 3 tutorials


We'll learn in machine learning
- Concepts
-Types of learning
-Supervised Learning
- Unsupervised Learning
- Data pre-processing, analysis and visualization
- Training data and test data
- Applications
- Regression
- Algorithms
- decision tree algorithm
- Support vector machines (SVM)
- Random forest
- Dimensional reduction algorithm
- boosting algorithms

Artificial Intelligence
- Introduction to Artificial Intelligence
- Intelligent systems
- Agents and environments
- Popular search algorithms
- Fuzzy logic systems
- Natural language processing
- Expert systems
- Robotics
- Neural networks

Also learn more about deep learning , Neural Network in detail

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Frequently Asked Questions(FAQ)

Who is this machine learning course for?

This machine learning course is for professionals aspiring to learn the complete picture of machine learning and artificial intelligence. It caters to the learning needs of both novice learners and experts.

What are the prerequisites for this course?

Students who have at least high school knowledge in math and anyone interested in machine learning can enroll in this course. Intermediate-level individuals who already know the basics of machine learning, including classical algorithms like linear regression or logistic regression, but wish to learn more about it and explore different fields of machine learning, can also benefit from this course. Additionally, those who are not comfortable with coding but are interested in machine learning and want to apply it easily on datasets can also join.

Who can start a career in Data Science with this course?

College students who want to start a career in Data Science can benefit from this machine learning course.

Who can level up in Machine Learning with this course?

Data analysts who want to level up in Machine Learning can enhance their skills through this course.

Who can become a Data Scientist with this course?

Individuals who are not satisfied with their current job and want to become a Data Scientist can acquire valuable knowledge from this machine learning course.

Who can create added value to their business by using powerful Machine Learning tools?

Any individuals who want to create added value to their business by using powerful Machine Learning tools can benefit from this course.

What will I learn in this app?

In this app, you will learn various topics, including why Python is chosen for Machine Learning, the Machine Learning Roadmap, Python 3 for Machine Learning, Artificial Intelligence, Introduction to Machine Learning, TensorFlow and Pytorch guides, Deep Learning, complete Machine Learning guides, Machine Learning Projects and Examples, and Python 3 tutorials.

What are the different types of learning covered in this course?

The course covers concepts such as supervised learning, unsupervised learning, data preprocessing, analysis, and visualization, training data and test data, and applications of machine learning.

Which algorithms will I learn in this course?

This course covers various algorithms, including the decision tree algorithm, support vector machines (SVM), random forest, dimensional reduction algorithm, and boosting algorithms.

What topics are covered in the section on Artificial Intelligence?

The section on Artificial Intelligence covers topics such as introduction to Artificial Intelligence, intelligent systems, agents and environments, popular search algorithms, fuzzy logic systems, natural language processing, expert systems, robotics, and neural networks.

Will I learn about deep learning and neural networks in detail?

Yes, you will learn more about deep learning and neural networks in detail in this course.