Udemy - Machine Learning Practical labs with Math's Core Foundation

[OneDDL]

[img]https://i115.fastpic.org/big/2021/0921/12/aca884d2e61285d184fd1dc56ea98612.jpeg[/img]
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 12 lectures (1h 44m) | Size: 602.1 MB
Machine Learning with Mathematics & Python Implementation (Course in progress)

[b]What you'll learn:[/b]
Understand the fundamentals of artificial intelligence and machine learning
Describe the methods of machine learning: supervised and unsupervised
Use the data analysis for decision-Making
Understand the limits of algorithms
Understand and grasp Python programming, essential mathematics knowledge in ML, basic programming methods
Knowledge of Calculus, especially derivatives of single variable and multivariate functions
Self-driving cars, Amazon Alexa, Catboats, recommender system, and many more
[b]Requirements[/b]
Fundamental knowledge of probability and linear algebra
The ability to code in any computer language, especially in Python language
Knowledge of Calculus, especially derivatives of single variable and multivariate functions
[b]Description[/b]
his Machine Learning course provides basic and advanced concepts of machine learning. Our course is designed for students and working professionals.
Machine learning is a growing technology that enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.
This machine learning tutorial gives you an introduction to machine learning along with a wide range of machine learning techniques such as Supervised, Unsupervised, and Reinforcement learning. You will learn about regression and classification models, clustering methods, hidden Markov models, and various sequential models.
This course will be useful for graduates, postgraduates, and research students who either have an interest in this subject or have this subject as a part of their curriculum. The reader can be a beginner or an advanced learner. This tutorial has been prepared for the students as well as professionals to ramp up quickly. This tutorial is a stepping stone to your Machine Learning journey.
Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
And as a bonus, this course includes both Python, R and MATLAB code templates which you can download and use on your own projects.
Kind Regards
Hafiz Muhmmad Attaullah
[b]Who this course is for[/b]
Anyone interested in Machine Learning.
Students who want to start learning 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 and Data Analyst.
Any computer science student hoping to broaden their skillset
Anyone interested in Machine Learning Including business leaders, managers, app developers, consumers - you!
Homepage

[code]https://www.udemy.com/course/machine-learning-practical-labs[/code]

[code]
https://hot4share.com/wb6th9i41iby/jpn2e.Machine.Learning.Practical.labs.with.Maths.Core.Foundation.rar.html
[b]Download (Uploadgig)[/b]
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