ALallanberger·Apr 17, 2018Submission
Top-down learning path on Machine Learning
3 points · Open discussionZuzooVn
machine-learning-for-software-engineers
AI & Machine Learning2016–2018
ZuzooVn / machine-learning-for-software-engineers
machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
9Distinct people
12Mentions
0Explicit recommenders
28.9KGitHub stars
What to know before exploring
What it is
A complete daily plan for studying to become a machine learning engineer.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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Also in these discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month12 dated mentions
Observed mentions: 2016-10-10 09:20:14 UTC to 2018-04-17 13:55:46 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Oct 2016 | 2016-10-01 00:00:00 UTC | 2016-11-01 00:00:00 UTC | 6 | 5 | 1 |
| Nov 2016 | 2016-11-01 00:00:00 UTC | 2016-12-01 00:00:00 UTC | 1 | 1 | 0 |
| Dec 2016 | 2016-12-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 1 | 1 | 0 |
| Jan 2017 | 2017-01-01 00:00:00 UTC | 2017-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2017 | 2017-02-01 00:00:00 UTC | 2017-03-01 00:00:00 UTC | 2 | 0 | 2 |
| Mar 2017 | 2017-03-01 00:00:00 UTC | 2017-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2017 | 2017-04-01 00:00:00 UTC | 2017-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2017 | 2017-05-01 00:00:00 UTC | 2017-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2017 | 2017-06-01 00:00:00 UTC | 2017-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2017 | 2017-07-01 00:00:00 UTC | 2017-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2017 | 2017-08-01 00:00:00 UTC | 2017-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2017 | 2017-09-01 00:00:00 UTC | 2017-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2017 | 2017-10-01 00:00:00 UTC | 2017-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2017 | 2017-11-01 00:00:00 UTC | 2017-12-01 00:00:00 UTC | 1 | 0 | 1 |
| Dec 2017 | 2017-12-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2018 | 2018-01-01 00:00:00 UTC | 2018-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2018 | 2018-02-01 00:00:00 UTC | 2018-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2018 | 2018-03-01 00:00:00 UTC | 2018-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2018 | 2018-04-01 00:00:00 UTC | 2018-05-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
12 sourcesSite to collect and share lists of resources around the internet like the ones on this page: https://github.com/ZuzooVn/machine-learning-for-software-eng...
In Ask HN: What are you working on?I've done Udacity's ML and doing the SDC in free time.
Short answer: Yes - I would do it again.
ML (Mid 2016):
Cost-wise you may be able to gather the similar quality of materials for free, nothing are too unique and in many cases additional intensive research are still required. But, the Udacity provides nice structure and helps you to keep motivated.
SDC (2016):
Much better experience for students, the quality of materials are higher, and amount of support from the peer group are extraordinary. Just one of the five projects in the first term are more complex than the whole ML nanodegree.
Haven't tried the AI nanodegree myself, but because it's a part of the new batch of programs I believe the experience would be quite positive (closer to SDC).
If you will decide to proceed with self-learning path, here is a nice multi-month study plan:
Read the rest
https://github.com/ZuzooVn/machine-learning-for-software-eng...
In any case I strongly advice to take a look into Andrew Ng's coursera courses and Andrew Karpathy's CS231n on CNN (http://cs231n.stanford.edu/) as a supportive materials.
Also, if money is the main concern, you may want to apply to sponsorship, or maybe discuss this with your current employer.
Feel free to PM me on twitter (same nick) if you have any other questions, would be glad to assist.
Top-down learning path: Machine Learning for Software Engineers
250 points · Open discussionMachine Learning for Software Engineers
444 points · Open discussionMachine Learning for software engineers at producthunt
1 points · Open discussionTop-down learning path: Machine Learning for Software Engineers
2 points · Open discussionTop-Down Learning Path: Machine Learning for Software Engineers
3 points · Open discussionThis link appeared on HN a few days ago:
https://github.com/ZuzooVn/machine-learning-for-software-eng...
Has some great links if you already have some knowledge about software engineering and want to get into Machine Learning
Josh Gordon from Google also has a extremely nice handson "how to start with Machine Learning" course on YouTube featuring scikit-learn and TensorFlow:
https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6r...
In Ask HN: How to get started with machine learning?Machine Learning for Software Engineers
1 points · Open discussionShow HN: Top-down learning path: machine learning for software engineers
1 points · Open discussion