<p>I do not have a definite answer for your question, but one way to validate your ML knowledge is to attempt certain problems that are asked in ML interviews for jobs. It might be a good starting point although it will not cover all the relevant concepts. Two such resources are</p>
<ul>
<li>The <a href="https://huyenchip.com/ml-interviews-book/contents/part-ii.-questions.html" rel="nofollow noreferrer">questions</a> section in Chip Huyen's ML Interviews book</li>
<li>A <a href="https://arxiv.org/abs/2201.00650" rel="nofollow noreferrer">Deep Learning Interviews</a> book  that contains many questions testing your ML and DL knowledge.</li>
</ul>
<p>If you are looking to solve more theory questions, you can work through the exercises of Bishop's <a href="https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf" rel="nofollow noreferrer">Pattern Recognition and Machine Learning</a> book, although I am not sure if the solutions are available online.</p>

CC BY-SA 4.0
2022-07-28T03:36:36.380Z
2022-07-28T03:36:36.380Z
Ganesh Tata
<ol>
<li><p>Find a high quality and well recognized course, you can pay extra for a Certificate:</p>
<ul>
<li><p><a href="https://ocw.mit.edu/search/?t=Artificial+Intelligence" rel="nofollow noreferrer">https://ocw.mit.edu/search/?t=Artificial+Intelligence</a></p>
</li>
<li><p><a href="https://www.edx.org/course/the-analytics-edge" rel="nofollow noreferrer">https://www.edx.org/course/the-analytics-edge</a></p>
</li>
</ul>
</li>
<li><p>Try answering some of these questions, network with others:</p>
<ul>
<li><a href="https://mathoverflow.net/search?q=views%3A5000..+answers%3A0+closed%3A0">https://mathoverflow.net/</a></li>
</ul>
</li>
<li><p>Write a few papers, publish, and try to obtain an <a href="https://arxiv.org/help/endorsement" rel="nofollow noreferrer">endorsement</a>.</p>
</li>
</ol>

CC BY-SA 4.0
2022-07-28T22:48:43.490Z
2022-07-28T22:48:43.490Z
Rob
<p>So I've been doing ML for ~2 years in industry, I'm a BSc in applied math, finished several courses on ML/DL on coursera, read some specific topics in ML/DL books. Seem to be in the know, more or less.</p>
<p>But the catch is: I've never <em>really</em> validated my knowledge, as in taken an exam or certification. Some time has passed since I read theory and I sort of think that I'm losing it (especially since all I did was time-series forecasting).</p>
<p>What are the possible ways to validate that I actually understand stuff? Do I just text random ML experts &quot;hey could I tell you stuff and you say whether that's bs or not&quot;?..</p>

<machine-learning><deep-learning><education>
How to validate my knowledge of models implementation, pros and cons and area of applicability?
Roman Nozdrin
# How to validate my knowledge of models implementation, pros and cons and area of applicability?

(Asked by: username_0 on 2022-07-27)

So I've been doing ML for ~2 years in industry, I'm a BSc in applied math, finished several courses on ML/DL on coursera, read some specific topics in ML/DL books. Seem to be in the know, more or less.

But the catch is: I've never *really* validated my knowledge, as in taken an exam or certification. Some time has passed since I read theory and I sort of think that I'm losing it (especially since all I did was time-series forecasting).

What are the possible ways to validate that I actually understand stuff? Do I just text random ML experts "hey could I tell you stuff and you say whether that's bs or not"?..

**Tags:** machine-learning, deep-learning, education


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## 2 answers

### Answer by username_1 on 2022-07-28. Score: 1

I do not have a definite answer for your question, but one way to validate your ML knowledge is to attempt certain problems that are asked in ML interviews for jobs. It might be a good starting point although it will not cover all the relevant concepts. Two such resources are

* The [questions](https://huyenchip.com/ml-interviews-book/contents/part-ii.-questions.html) section in Chip Huyen's ML Interviews book
* A [Deep Learning Interviews](https://arxiv.org/abs/2201.00650) book that contains many questions testing your ML and DL knowledge.

If you are looking to solve more theory questions, you can work through the exercises of Bishop's [Pattern Recognition and Machine Learning](https://www.microsoft.com/en-us/research/uploads/prod/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf) book, although I am not sure if the solutions are available online.


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### Answer by username_2 on 2022-07-28. Score: 0

1. Find a high quality and well recognized course, you can pay extra for a Certificate:

   * <https://ocw.mit.edu/search/?t=Artificial+Intelligence>
   * <https://www.edx.org/course/the-analytics-edge>
2. Try answering some of these questions, network with others:

   * [https://mathoverflow.net/](https://mathoverflow.net/search?q=views%3A5000..+answers%3A0+closed%3A0)
3. Write a few papers, publish, and try to obtain an [endorsement](https://arxiv.org/help/endorsement).


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