Kirill Eremenko
Interested in the field of Machine Learning? Then this course is for you!
This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms, and coding libraries in a simple way.
We will walk you step–by–step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub–field of Data Science.
This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:
Part 1 – Data Preprocessing
Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Part 3 – Classification: Logistic Regression, K–NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Part 4 – Clustering: K–Means, Hierarchical Clustering
Part 5 – Association Rule Learning: Apriori, Eclat
Part 6 – Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
Part 7 – Natural Language Processing: Bag–of–words model and algorithms for NLP
Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
Part 9 – Dimensionality Reduction: PCA, LDA, Kernel PCA
Part 10 – Model Selection & Boosting: k–fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
Instructor Details
Courses : 11
Specification: Machine Learning A-Z : Hands-On Python & R In Data Science
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35 reviews for Machine Learning A-Z : Hands-On Python & R In Data Science
Add a review
| Price | $12.99 |
|---|---|
| Provider | |
| Duration | 44.5 hours |
| Year | 2020 |
| Level | All |
| Language | English ... |
| Certificate | Yes |
| Quizzes | Yes |
$12.99
Varad Sawant –
It’s nice
Vishnu –
It was a good match for me…The course has been very simple and straightforward as of yet.
Mariusz Bruj –
I find it very interesting and useful. I am beginner to this topic so providing step by step instructions work for me very good!
Danish Sheikh –
It was an excellent experience .I learned a lot through this course and surely recommend this to other as it does a great job in teaching beginners.
Joshua Cookhorne –
I gave up on coding because it was hard, but this is giving me hope again.
Sagiv Reuben –
it was a purity strata forward I will defiantly will have to go back to remember all thews packages and functions if the is one thin that was annoying is the volume of the narrator it was vary low I had to turn the volume meter all the way on both the video and the computer.
Monika Behera –
The course pretty much covers everything
Daniel Lowenthal –
This course gives an extremely superficial explanation of various ML methodologies and then shows videos of someone using a python library to apply those methodologies to varius data sets. None of the algorithms are built from scratch (i.e. it’s all just import library X). If you have even a basic knowledge of programming and of mathematics, this will be a complete waste of your time. Needless to say, look elsewhere if your goal is to prep for an interview or a job in ML.
Bruce Greentree –
easy to follow and interesting.
Amandeep Kaur –
yes its very interesting
AltTabber –
Outdated lessons
Muralidhar –
Very Good explanation and programming procedures.
Kwame Obeng Sasu –
I had a great feeling starting this course and day in and day out there’s something new to learn.
Wisdom chibeze –
I scanned the pdf that covers course curriculum which also enlisted solutions to anticipated errors per lecture. To me, that in itself is worth a 5 star rating. I’ve taken about 10 bestseller courses and none of them has done this.
Kumar Ranjan –
really good
Mitali –
It s extremely easy to understand
Abhishek Banerjee –
yes
Woody Davis –
So far it all feels a little cheesy
Rakesh Bhatt –
Later
Parakh Jain –
It is very interesting, the instructor is having superb pedagogic skills..
Lightman –
Perfect
Fabrizio Alberto Mor –
Courses are outdated, I get that they add patches to it but it just feels really lazy of them to not redo the parts of video where the code is old.
Andres Posada –
This course really teaches the most relevant topics about ML, explaining the difficult concepts with simple examples making it easy to understand and implement. Yet, if you are interested in the fundamentals and more mathematic explanation, within the course you will find the best references to papers and books that will complement your knowledge. Este curso ense a los t picos m s relevantes de ML, explicando conceptos complejos con ejemplos simples y de alta recordaci n. Adem s incluye el paso a paso para la implementaci n de los ejemplos tanto en Python como en R. Si el alumno requiere una mayor profundizaci n en cuanto a los conceptos, el curso trae material de referencia de excelente calidad.
Sanath Ramachandra –
Most of the code used during the course is outdated, an instructor has uploaded few codes but not all of them. so we really need to dig few stuffs in the internet
Trevor Antonio –
Loving this course so far!
Nam Nguyen –
I learn 3 more options to run Python code with different tools such as Google colab, Spider and Jupyter
Muktar Ismail Nouh –
wonderfull
Priya Sankar –
So far it is easier and very systematic content
Song Li –
I love this step by step way of teaching machine learning, especially for people of my background I know statistics but have zero experience in coding. Thank you. I’ve browsed through many ML online courses, you are the only one who teaches machine learning coding step by step!
Sebastian –
Great course!
Debashree Tagore –
It was good. The video could have been made a bit more interesting
Venkata Devi Prasad K –
As of now going though NLP and very interesting and nice way of explaining in simple language.
Subi Babu –
Good for beginners and professionals
Anupam Dubey –
The theoretical aspects of every method could be more elaborated upon.
Cathy Zeng Earnshaw –
The explanation of the regression is pretty clear. Much better than my prof.