Sundog Education by Frank Kane
New! Updated for Winter 2019 with extra content on feature engineering, regularization techniques, and tuning neural networks – as well as Tensorflow 2.0!
Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. Data Scientists enjoy one of the top–paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That’s just the average! And it’s not just about money – it’s interesting work too!
If you’ve got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry – and prepare you for a move into this hot career path. This comprehensive machine learning tutorial includes over 100 lectures spanning 14 hours of video, and most topics include hands–on Python code examples you can use for reference and for practice. I ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn t.
Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. It s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference. You won’t find academic, deeply mathematical coverage of these algorithms in this course – the focus is on practical understanding and application of them. At the end, you’ll be given a final project to apply what you’ve learned!
Instructor Details
Courses : 7
Specification: Machine Learning, Data Science and Deep Learning with Python
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45 reviews for Machine Learning, Data Science and Deep Learning with Python
Add a review
| Price | $12.99 |
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| Provider | |
| Duration | 14.5 hours |
| Year | 2020 |
| Level | Beginner |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
$12.99
Ram Krishna –
Not very explanatory
Maalaiappan S –
So good so far..
Nihal –
Just the basics of Data Science.
Charan Ram –
Absolutely
Sahaj –
The course has been pretty good so far, but some of the topics have not been fully explained, for example, the plotting data on histograms. I had to do quite a bit of research to fully understand why some graphs would plot and some would return errors.
Nirmal Kumar –
Very much satisfied by the method of coaching. Frank explains every concept and each line in code slowly, clearly and to the point. Lot of practical examples are given. Wide area of concepts are covered. Definitely recommended.
Agbamoro Victoria –
Yes, being a beginner, I really appreciate how he starts from the very basics and it’s fun to learn.
Kelley Smit –
Love the practical examples and the level of detail provided to have full understanding of each topic
Prachi . –
its bit fast
Lanittah –
I love finding a course that goes over libraries and python and putting deep learning into a no nonsense learning approach.
Ryan Cameron –
This is great so far! The speed is perfect. The constant reminders are good too. It takes people 2 or 3 times to remember something and he does a good job of hitting that home.
Infine –
brilliant course! I’ve got much more than expected. Thank you Frank!
Nidhi –
Informative
David Meyer –
I was fairly familiar with all these steps but if I had this kind of instruction first, it would have saved me a ton of time googling and self teaching. Great instruction
Shankar Veerashetty –
So far so good.
Kiran Kumar Motheram –
Perfectly Awesome! Indeed Fran Kane is the very instructor I was looking for. As if I am eating a peeled banana, he is making Data Science simple to learn. Thanks Frank Kane!
Blake Heimann –
I enjoyed this course because it was a very good introduction to machine learning. It contained a good balance of theory and actual python code. By the end of the course, I was able to construct multiple different machine learning techniques with confidence!
Tirth –
Udemy doesn’t even deserve this. Every video of my course is buffering at 480p resolution at 15 mbps internet speed. For your kind information I am able to stream 4k resolution video on youtube with same internet connection on the same device.
Michael Webb –
It is still a little early in the course but I like it so far.
Rick Nguyen –
I have a background in programming but this is all new to me. So far so good.
Fekade Tegeghe –
It is very nice. I enjoyed the course very well. Particularly, I like Frank’s creativity in creating examples and handling concepts to make much easier.
Ganesan –
Wise to have classes like this. Subject illustrated well with concise advice on setting up the system.
Prashant Shukla –
everything is smooth till now !!
Triv112 . –
This course was a very helpful introduction
Reena Abraham –
yes
Joaquin Real Llanderal –
Well structured course. It is nice that the lecturer has a clear accent and a non monotonous tone. The mathematical/statistical concepts are explained well. The examples are also applied well with the Jupyter notebook tools.
Sanket K –
It was Exciting and explanation was very clear
Olusola Odurinde –
i am enjoying the course. Good presentation skills. Voice very clear
Mhommed Tarek –
Amazing course. It gets you to get some experience and pretty easy to understand thanks to the amazing teaching. Solutions are provided for everything so that you don’t get stuck in a question. Also like how he gets you from the basic math to implementing a neural network on your own. Had great experience
Ola Younis –
good explanation
DASGUPTA –
Very nice articulation and easy to follow
Mallugalla Bhumika –
SIR IS SO FAST IN EXPLAINING WITH WHICH I WAS SO DISAPPOINTED.I DID NOT UNDERSTAND CONCEPTS CLEARLY.
David Schult –
easy to follow
Roshan Kumar –
Needs more practice example to understand the topic.
Anguluri Karunyamruta Subash –
just started now.Upto now it is good.
Risso –
Will tell..at this very beginning moment have no a lot to say…just some troubleshooting as Q&A said about the python version for tensorflow
Niall Xie –
The tutorial is very good. it could have been the perfect tutorial for me, had the tutorial worked in the same version as i am working on.
Darshana Enugandula –
There is always room for more
David Johnson –
I am enjoying this course.
Eduard Lazar –
No 3.8 anaconda follow through , no biggie but couldn’t install tensorflow and had to resort to anaconda help which differs significantly
Rama Anant Vishwamitre –
Course covers all basic knowledge about ML.
Msingathi Majola –
I think it’s very nice that you walk us step by step in getting started.
Karthikeyan Venugopal –
Lots of information made easy to learn. It is more than i expected and really is helpful.
Daniel Pegu –
It’s a good match. I am learning things pretty fast.
Kamala Marepalli –
Would have been much more better if there had been a deeper introduction of what is machine learning, Data science and deep learning and what is python…. In sundog MLCourse materil there is no jupyter notebook to install from it. However explanation is good.