Advanced Machine Learning

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Below are the top discussions from Reddit that mention this online Coursera specialization from National Research University Higher School of Economics.

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods.

Recurrent Neural Network Tensorflow Convolutional Neural Network Deep Learning Data Analysis Feature Extraction Feature Engineering Xgboost Bayesian Optimization Gaussian Process Markov Chain Monte Carlo (MCMC) Variational Bayesian Methods

Accessible for free. Completion certificates are offered.

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Taught by
Evgeny Sokolov
Senior Lecturer
and 20 more instructors

Offered by
National Research University Higher School of Economics

This specialization includes these 7 courses.

#612
Introduction to Deep Learning
The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding.
National Research University Higher School of Economics
Evgeny Sokolov
0 reddit posts
5 mentions
#153
How to Win a Data Science Competition
Learn from Top Kagglers
If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language process...
National Research University Higher School of Economics
Dmitry Ulyanov
1 reddit posts
12 mentions
#438
Bayesian Methods for Machine Learning
People apply Bayesian methods in many areas: from game development to drug discovery.
National Research University Higher School of Economics
Daniil Polykovskiy
0 reddit posts
8 mentions
#475
Practical Reinforcement Learning
Welcome to the Reinforcement Learning course.
National Research University Higher School of Economics
Pavel Shvechikov
1 reddit posts
6 mentions
#926
Deep Learning in Computer Vision
Deep learning added a huge boost to the already rapidly developing field of computer vision.
National Research University Higher School of Economics
Anton Konushin
0 reddit posts
1 mentions
#357
Natural Language Processing
This course covers a wide range of tasks in Natural Language Processing from basic to advanced: sentiment analysis, summarization, dialogue state tracking, to name a few.
National Research University Higher School of Economics
Anna Potapenko
0 reddit posts
9 mentions
#825
Addressing Large Hadron Collider Challenges by Machine Learning
The Large Hadron Collider (LHC) is the largest data generation machine for the time being.
National Research University Higher School of Economics
Andrei Ustyuzhanin
0 reddit posts
3 mentions

Reddit Posts and Comments

4 posts • 61 mentions • top 19 shown below

r/learnmachinelearning • post
18 points • Whencowsgetsick
Has anyone taken the Advanced Machine Learning specialization on Coursera?

Has anyone taken the Advanced Machine Learning specialization on Coursera? I'm referring to this one: https://www.coursera.org/specializations/aml. It seems more practical and quotes a longer time than Andrew's Ng DL specialization so I was wondering how it is

r/learnmachinelearning • post
13 points • bandalorian
Does anyone know if the advanced machine learning specialization (10 month program) from Coursera is good?
r/datascience • comment
18 points • Rezo-Acken

Well here is what I'm currently doing after having finished all the basic stuff in ML/DL + a MS in stats: https://www.coursera.org/specializations/aml and https://web.stanford.edu/class/cs224n/

There is also a course for computer vision.

These courses are graduate level but dont require a PHD. Now, finding a job that require this is harder (without PHD and outside tech giants) but from what I've seen it's because most analytic/data science department simply have no clue. I was able to work on an NLP project where I'm at because I brought it forward (it's not a complicated NLU problem mind you ;))

r/datascience • comment
4 points • Artgor

If you know Russian, then machine learning specialization by Yandex and MIPT on Coursera is really the best one. It covers a lot of topics: classification, regression, clustering, visualization, nlp, recommenders, statistics, time series and other things.

And now there is an advanced specialization by Yandex and Higher School of Economics - https://www.coursera.org/specializations/aml It is in English and quite difficult. It covers such topics as Deep Learning, Kaggle, Bayesian methods, Reinforcement learning, NLP and others.

r/learnmachinelearning • post
7 points • abed_the_drowsy_one
is ADVANCED MACHINE LEARNING specialization (coursera) worth it ?

good day people, i was wondering if advanced machine learning sepc from coursera ( https://www.coursera.org/specializations/aml ) is worth the 50 dollars a month, i haven't seen any reviews for it around so i thought i would ask here.

much appreciated.

r/datascience • comment
1 points • lambdaofgod

I recommend Advanced Machine Learning specialization from Coursera. It covers stuff you mentioned (trees etc) and much more, like Bayesian methods (for example they cover Bayesian Optimization which is pretty useful in practice). The only problem is that specialization is all over the place, and some courses (CV course last I checked) have poor assignments - they're so underspecified that completing them is bordering impossible.

r/Python • comment
1 points • ACrispWinterDay

I didn't say you were being disingenuous, I said it would be disingenuous to say that. The person in question said they wanted to pick up a new skill in ML, so based on that information I would assume they had no experience, and would benefit more from learning basic libraries and applications in of ML in Python. You responded to my comment that you felt like you were totally comfortable applying the skills you learned in a couple weeks of the course, and left out the part that you already had extensive experience in Python data analysis, so you are clearly not in the same boat as the OP.

At a high level, yeah jumping around languages is not a big deal. But this is a Python forum, Python is the language of ML nowadays, and I don't see the controversy in pointing out that a theoretical course in Octave is not a terribly good answer for someone looking for a Python course. And, by the way, there is also several deep theoretical courses in Python on Coursera with much better coursework then Andrew Ng's Machine Learning, I prefer this one (https://www.coursera.org/specializations/aml). Much longer course, but goes into much more depth, is more along the lines of combining Andrew Ng's Machine Learning course and his Deep Learning specialization, but with Python notebooks straight from the beginning. I don't think the Andrew Ng course is bad, it's just seriously overrated because it's been around a long time so even people who know almost nothing about ML know about the course.

r/learnmachinelearning • post
3 points • alexgmcm
Advanced Machine Learning Specialisations: NRU vs. Google?

I am interested in taking one of the Advanced Machine Learning specialisations on Coursera.

I have previously done Andrew Ng's ML and DL courses, Koller's PGM one and I use ML occasionally at work so I have some experience and would like to go beyond the basics.

I am trying to choose between these two:

The Google course has the benefit that it is using GCP which we use at work but I'm concerned it might be more of a sales pitch for Google's products rather than a great educational course. (I have seen some Google ML courses that were basically just showing you how to use Google's pre-trained models in your apps)

The NRU one has the downsides that I'm not sure of the quality of the course and perhaps it won't be as useful but at least they don't have an incentive to tie you into certain tools.

Has anyone taken any of these courses (or any similar) and can recommend/review them?

r/datascience • post
1 points • quantum_booty
ML Engineer Career Advice

Hi there,

I am a recent graduate in Physics, and I would like to enter the fields of Data Scientist and Machine Learning. My aim is to self-study in this period of quarantine and hopefully land a intern or entry level job in this field. I would like advices from you guys regarding what I need to learn and do in order to make this happen. I have recently completed the ML course by Ng, implementing it in Python rather than Matlab. I plan to familiar myself with the Scikit learn library, as well as SQL, and start doing kaggle competitions. Also, I am going to start the Advanced Machine Learning specialization on coursera.

Furthermore, to suppliment the practical ML with theory, I am reading All of Statistics by Wasserman, and I plan to also read Element of Statistical Learning after.

Do you think what I am doing right now is a good use of my time? Do you think this is enough for me to land a entry level job? It seems that even "entry level" job requires a good amount experience and degrees like CS, ML or mathematics. Do you think what I am doing will make me standout against the masters and PhDs?

Thank you!

r/learnmachinelearning • post
1 points • quantum_booty
Machine Learning Engineer career advice

Hi there,

I am a recent graduate in Physics, and I would like to enter the fields of Data Scientist and Machine Learning. My aim is to self-study in this period of quarantine and hopefully land a intern or entry level job in this field. I would like advices from you guys regarding what I need to learn and do in order to make this happen. I have recently completed the ML course by Ng, implementing it in Python rather than Matlab. I plan to familiar myself with the Scikit learn library, as well as SQL, and start doing kaggle competitions. Also, I am going to start the Advanced Machine Learning specialization on coursera.

Furthermore, to suppliment the practical ML with theory, I am reading All of Statistics by Wasserman, and I plan to also read Element of Statistical Learning after.

Do you think what I am doing right now is a good use of my time? Do you think this is enough for me to land a entry level job? It seems that even "entry level" job requires a good amount experience and degrees like CS, ML or mathematics. Do you think what I am doing will make me standout against the masters and PhDs?

Thank you!

r/MLjobs • post
0 points • bandalorian
Does anyone know if the advanced machine learning specialization (10 month program) from Coursera is good?
r/datascience • comment
1 points • failarmyworm

I'm ~halfway through this Coursera specialization and it's been a pretty good experience so far: https://www.coursera.org/specializations/aml

It could also be a good idea to take courses that give you more domain knowledge, or general statistics. Even though I had taken university-level probability courses and had done quite some data science already I still learned quite some new concepts from this course (e.g. how to make plausible claims of causality): https://www.edx.org/course/data-analysis-for-social-scientists-1 It also covers some visualization. (Also one week covers machine learning - I found those lectures a bit disappointing but the rest was quite good.)

r/MLQuestions • comment
1 points • ivivek11

Coursera Advance Machine learning - https://www.coursera.org/specializations/aml

r/learnmachinelearning • post
14 points • aka_ab31
Advice and Suggestions needed on my Roadmap to Machine Learning/AI Pro

I found out recently that ML and AI has interested me so much. I have decided to take up a career in it. Before we begin, I would like to tell a few things about myself that might help you in assisting me better. I am guy who loves to learn stuff but the bad part is I don't put enough time to learn them fundamentally. I get bored with watching lengthy videos online and jump into the project directly without learning the basics properly and learn what's only necessary or most times just google up the problem/error and get it done. I have always expected quick results and gave up easily when they don't happen. I have understood that it won't be of any use in ML/AI learning. So I have decided to create a roadmap and follow it to become a ML/AI pro. I am really bad at Math.. I was good at programming but stopped practising it.. So it is better to call myself a noob in both programming and Math. I am including the links to the courses if anybody would like to follow. The ' | ' means that I will work on it simultaneously.

  1. Python for Everybody from Coursera | Code Academy Python Tutorials | Sentdex Python Tutorials
  2. Trignometry from Khan Academy | Pre Calculus from UCI Open
  3. Calculus from Khan Academy | Single Variable Calculus from MIT
  4. Multi Variable Calculus from Khan Academy | Multi Variable Calculus from MIT
  5. Linear Algebra from Khan Academy | Linear Algebra from MIT
  6. Mathematics for Machine Learning from Coursera
  7. Statistics from Khan Academy | Introduction to Probablity and Statistics from MIT | Statistics from Udacity | Introduction to Probablity and Data
  8. Data Structures from Coursera | Intro to Algorithms from Udacity | Algorithms from Coursera
  9. Machine Learning from Coursera | Intro to Machine Learning from Udacity | Foundations of Machine Learning by Bloomberg
  10. Learning from Data from Caltech
  11. Kaggle Competitions | Hacker Rank | Other ML applications and Projects
  12. Intro to AI from Udacity | Deep Learning from Coursera | Fast AI
  13. Advanced Machine Learning from Coursera | Machine Learning from Tensorflow on GCP

I am planning do it this time without giving up. I am taking the courses of same level from different platforms to get better exposure and understanding. I will skip the parts that are the same. What do you guys think? Do you think it is a overkill? Are the courses in the right order? Will it help me get good knowledge on ML/AI? Feel free to leave your advice or suggestions.

I will be able to dedicate 30-35 hours per week towards this. Assuming me to be a slow learner, how long would it take for me to have good command in ML/AI?

Apart from these I also wish to learn MatLab, LabView, Tableau and R. Thank you for taking the time to read this post.

r/greece • comment
1 points • onetwosex

Αν θες για machine learning, κοίταξε στο Coursera. Τόσο για τα μαθήματα του Andrew Ng (machine learning, deep learning [deeplearning.ai]), όσο και αυτά του National Research Higher School of Economics. Το machine learning είναι τσάμπα. Τα άλλα κοστίζουν κοντά €44/μάθημα.

Επίσης μπορείς να τσεκάρεις και το fast.ai, που είναι δωρεάν. Και έχει το προτέρημα πως αντί για Tensorflow σε μαθαίνει Pytorch, που είναι πιο εύκολο για αρχάριους imho. Και εστιάζει λιγότερο σε θεωρία και περισσότερο σε πρακτική.

Source: έχω παρακολουθήσει τις πρώτες 3 βδομάδες του fast.ai, και το μισό machine learning του Andrew Ng. Ζαχαρώνω καιρό το deeplearning.ai, αλλά σκέφτομαι τα €€.

Θα έμενα μακρυά από τα e-learning προγράμματα του Καποδιστριακού. Μου φαίνονται πολύ ακριβά και μόνο για εσωτερική (εγχώρια) κατανάλωση.

r/learnmachinelearning • comment
1 points • MTMD36

People generally recommend "Machine Learning" by Andrew Ng on Coursera. It's in Octave, but people have done it in Python:

E.g. this person:

https://github.com/dibgerge/ml-coursera-python-assignments


Could also try this chunky specialisation by some Russian uni:

https://www.coursera.org/specializations/aml?specialization=aml


Like the other guy said, read sklearn documentation if you want to do Python. But instead of reading it as its own thing, I'd say use it as a reference personally. But that's maybe because I learn better with videos.


If you want to try and understand Bayesian shit, look here:

https://github.com/avehtari/BDA_course_Aalto


This guy posted a "super harsh" guide:

https://www.reddit.com/r/MachineLearning/comments/5z8110/d_a_super_harsh_guide_to_machine_learning/


For supplementary videos on understanding a topic, you could look up "Machine Learning Summer School" on YT and search through looking for things you might find interesting.

E.g. 2 videos on Gaussian Processes by Neil Lawrence, below is part 1 (but seems shite according to the comments because of some slide issues, but this is just an example)

https://www.youtube.com/watch?v=U85XFCt3Lak


I suppose it depends what you want to learn. What's your endgame here? Like what is the sort of job you're after?

r/learnmachinelearning • post
1 points • mallasahaj
Suggestions, please

After tons of research, here is the list of courses that I think are good for me. I want to make my own AI projects to help society benefit from it.

  1. Algorithm about machine learning
  2. Python course
  3. Mathematics for machine learning
  4. Applied data science with python
  5. Deep learning
  6. TensorFlow in practice
  7. Advance Machine learning

After these, I'm planning to do some of my own ML projects. Can you suggest to me if the order of the courses is good or suggestions on which course should I apply or not?

Thanks!

r/learnmachinelearning • post
3 points • do-on
Catalog for Machine learning degree.

I am passionate to learn about deep learning specifically i want to learn about natural language processing....because i want to build my jarvis. Currently i am pursing Btech from India and i am sophomore. The issue i am facing is that i have nobody to guide me and i get distracted very easily. Following my interest i started deeplearning.ai specialization from coursera. Now that i have completed second course i feel like i can not recall many of the things which was taught to me. Therefore now i have decided to make a catalog of course and to start from basics covering all the way to advance. I have also started competitive coding because i love problem solving.

​

I am listing few courses which i found are useful, can anyone please develop a catalog so that i can focus and following to become machine learning engineer.

​

Foundation courses

  1. https://in.udacity.com/course/programming-foundations-with-python--ud036
  2. https://in.udacity.com/course/intro-to-data-science--ud359
  3. https://www.coursera.org/specializations/data-science-python (Specialization)
  4. https://www.coursera.org/learn/machine-learning?

Advanced courses

  1. https://www.coursera.org/specializations/deep-learning/?siteID=EBOQAYvGY4A-CZk7TATLvBfdZnDu2EmtDg&utm_content=3&utm_medium=partners&utm_source=linkshare&utm_campaign=EBOQAYvGY4A
  2. https://github.com/simoninithomas/Deep_reinforcement_learning_Course
  3. https://www.coursera.org/specializations/aml
  4. Fast.ai

Ps: I can only opt for the courses which are free or they have scholarship available like coursera.

r/TechSEO • comment
1 points • bucaroloco

Hi Rebboc,

>Are there NJ stereotypes that are absolutely true of where you live?

I just Googled a few to see which ones are true where I live (Central Jersey).

  1. Jersey people are indeed very proud and love living here. I will say "maybe" as proud as Dominicans. Do you remember the Boston world series where the players wave the Dominican flag? Yes. We are very proud.
  2. We are a massive bagel and pizza, eating crowd. I see one shop every corner.
  3. Everybody references the place they live off an Exit in the Parkway. My exit is 11, BTQW
  4. We struggle to pump gas by ourselves when visiting other states :)

​

>Python seems to be gaining some traction in the tech SEO world (JR Oakes's hangout earlier this week is a good example of interest). Are there resources or examples you're excited about that you'd point an advanced Python user towards for SEO purposes?

Yes. I was in attendance and it was a really great job by JR!

Absolutely. Advanced Python users should focus on deep learning and/or automation. Either path will provide plenty of challenging problems.

This is the path I took to learn deep learning.

  1. I completed this specialization https://www.coursera.org/specializations/deep-learning
  2. Then, I completed this other one https://www.udacity.com/course/deep-learning-nanodegree--nd101
  3. I started this one (really challenging) https://www.coursera.org/specializations/aml, but haven't had time to finish it. The NLP module is gold.
  4. These courses will give a strong foundation and you can learn new stuff from reading the actual papers. I like this site to keep track of the latest stuff https://paperswithcode.com/
  5. Make sure to check my articles! The latest one for Search Engine Journal shows you how to execute JavaScript from Python and create awesome visualizations https://www.searchenginejournal.com/uncover-powerful-data-stories-python/328471/

​

>Finally, is there anything up and coming in the SEO or tech worlds that you're looking forward to, whether events, technologies, tools...?

​

I'm really excited about text generation and see incredible and fast progress in this area. I gave a webinar for DeepCrawl and more recently shared an example of what is now possible https://www.linkedin.com/posts/hamletbatista_ai-text-generation-activity-6581207906635575296-pSZA