Codestars by Rob Percival
The Complete Machine Learning Course in Python has been FULLY UPDATED for November 2019!
With brand new sections as well as updated and improved content, you get everything you need to master Machine Learning in one course! The machine learning field is constantly evolving, and we want to make sure students have the most up–to–date information and practices available to them:
Brand new sections include:
Foundations of Deep Learning covering topics such as the difference between classical programming and machine learning, differentiate between machine and deep learning, the building blocks of neural networks, descriptions of tensor and tensor operations, categories of machine learning and advanced concepts such as over– and underfitting, regularization, dropout, validation and testing and much more.
Computer Vision in the form of Convolutional Neural Networks covering building the layers, understanding filters / kernels, to advanced topics such as transfer learning, and feature extractions.
And the following sections have all been improved and added to:
All the codes have been updated to work with Python 3.6 and 3.7
The codes have been refactored to work with Google Colab
Deep Learning and NLP
Binary and multi–class classifications with deep learning
Get the most up to date machine learning information possible, and get it in a single course!
Instructor Details
Courses : 13
Specification: The Complete Machine Learning Course with Python
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18 reviews for The Complete Machine Learning Course with Python
Add a review
| Price | $17.99 |
|---|---|
| Provider | |
| Duration | 17.5 hours |
| Year | 2020 |
| Level | All |
| Language | English ... |
| Certificate | Yes |
| Quizzes | Yes |
$17.99
Abdul Ahad –
Excellent
Irene P rez –
For the moment is it really slow, not on the content but on the way of speaking. Other courses are much better organized in each video, they don’t need to make it so long
Nitish Srivastava –
its just start.. i just want to know if i have to start a project from scratch … how can i manage development process
Avinash Kumar –
Server respone is very slow.
Matthew Thyer –
Very good. Anthony explains each step quite clearly. He may have missed a step where the student should download the course materials to a folder on their dekstop as I had only made a copy in my Google drive and it wasn’t clear that Anthony was about to work with a copy on the desktop. (He said you could download to your computer, not that you needed to for the next steps).
Alexis Javor –
Good visibility on mobile, though would probably prefer to check it out on laptop for practical purposes. So far, I m enjoying it!
Akila Krishnadoss –
I am a web developer with no experience in machine learning. I find this course very useful because of the following reasons 1.The author jumps in to the code(more hands on) and with out going in to too much theory. 2.Side by side he throws light on statistical key concepts with out going in too much detail 3.As a beginner I did not feel overwhelmed in spite of the topic being so big. 4.He fixes the errors right away showing how easy it is troubleshoot.
Russell Ritenour –
Not yet. Too long in the basics, but probably necessary for a general audience.
Don –
Goodly coding.
Prerit Tripathi –
i felt that sometime course flow was disturbed.
Maridella Javal –
I learned a lot from these videos.
Arnab Bhattacharyya –
It was very good and informative
John Romeo Graham –
This is an awesome course. The instructions and labs are very clear and easy to follow
Ahmed Dawoud –
Very poor course, the instructor is basically running the previously prepared notebooks, he seems very unfamiliar with core concepts of machine learning
Yan Yang –
Lack of detailed description of underlying algorithms
Jayesh Jayakumar –
The course have gave an insight about what Machine learning is about, the capabilities, the opportunities etc.
Shashank Kulkarni –
This was a great experience learning and doing some awesome hands on projects
Sulfikar Ali Nazar –
Instructor good at focusing on the topic and explaining the concepts very well.