Hi everyone today we are going to be talking about how to move from software engineering to machine learning in the past three months I have been reading up a lot about machine learning. Some of the findings have surprised me So I’ll try to break this down into let’s say five important tips The first thing is not to get lost in all the hype There’s a lot of blog posts articles that I read and they are all about the consequences of machine learning as an engineer Who wants to learn something? We are not really too bothered about the consequences right now Just just focus on getting the basic models working you know a person who can’t write hello world can’t really think about taking over factories The second point which I think is quite important is not to get lost in all the math behind these models these machine learning models And I know this is controversial and might sound you know completely wrong But I started from support vector machines went to quadratic programming Which in turn is based on the simplex method? it’s a part of operations research when I started coding this it’s going to have bugs because we are software engineers if you want to use a machine if you want to use a model you can use it also like an Interface as in you given some inputs and get some outputs Yeah, you get some work done instead of understanding how it’s working internally Now if your purpose is academic or if your purpose is to go through a degree You have the time to spend understanding this model in depth But my personal experience is that when I try to learn machine learning this way, I mean understanding all the mathematics It’s like a rabbit hole. I get lost at number three play to your strengths if your data engineer then Consider this to be an extension of the problem that you have, you know collecting data is something that you do really well Inferring from it is something that you need to do now, which is what machine learning entirely is but at least the parts where you collect data and clean it or filter it out that data is something that you have been dealing with for a really long time if You are an algorithm person, then you can start thinking about all the approximation algorithms You have used possibly in programming contests possibly in college to understand How does a machine learning model behave or how do you actually evaluate its performance? So if you if you play to your strengths and play to things that you already understand your mind is far more Accepting of some new information instead of completely different information Point number four is something that this channel will help you with It’s finding reliable sources the sources that I use are either company blog posts Let’s say uber Google Facebook what these guys do is they write in terms of software engineering. It makes a lot of sense again it’s like playing To Your Strengths but also these companies they don’t hype things as much as They possibly could the second thing is that because it’s a practical case of machine learning. There’s a lot of decisions that people make before using a particular model instead of you know Taking a toy problem and then deciding on how to solve it with different ways point number five Which is probably the most important and although people know it they don’t do it is coding you need to implement machine learning algorithms to understand it in depth unless you Start coding on the terminal you won’t be able to play around with that kind of model And of course, you won’t get the confidence of actually having programmed that machine learning code now There are a lot of courses online for machine learning A lot of them are quite good also there’s Udacity, there’s Kaggle, there’s Coursera but there’s one specific machine learning course created by educator for software engineers and once I found it I mean I didn’t waste any time to collaborate with them and make sure that our community gets a discount for this machine learning for software engineers is really nice because it moves Towards the coding bit initially and then you can get into the concepts So there’s some results and outputs that you can see while you’re making the transition to machine learning I actually like the way they focus on the pandas library before getting into the complex clustering and other algorithms the best thing is if you go through this channel and use the coupon code GS ml 20 Then you get a 20% discount, but this is a limited offer So the first 50 users are only going to get this and of course you can guess what GS stands for So those are the five tips I’d like to leave you with to transition from software engineering to machine learning if you have any doubts or suggestions You can leave them in the comments below. Of course, you might have your own opinions you can leave that also in the comments below if you like the video then hit the like button and if you want notifications for Further videos like this hit the subscribe button. I’ll see you next time


Bianca A. - There's art to data science · May 4, 2019 at 5:40 pm

Great advice. There's only one part I don't agree with: the part where you talk about the need to understand the ML math. I think it's very important to understand that math. The problem is that, like you saw, most math material is either too vague or too detailed for someone who's starting ML. So I think it's best to do the steps you mentioned (start coding right away, using ML models right away, etc) and give yourself more time to learn the math. Take it slowly.

With a good learning plan and good study habits, you can learn in less than a year the math (linear algebra, calculus, and statistics) needed for ML. Once you do that, you'll feel so much more confident in your work.

For example, I'm sure you don't regret learning about SVMs. You just wish the material was better organized and better explained. πŸ˜‰

Anyway, great video. I always learn something new from you. Keep up the great work.

Shivaprasad B · May 14, 2019 at 9:30 pm

Great going . I am curious as to how do you find time to study all these new things along with your daily job ? Tips here would be helpful. Probably a video just covering this πŸ™‚

Mohit Varma · May 15, 2019 at 4:10 am

At the starting you said learning maths behind algorithms is like going into a rabbit hole where one tends to get lost,it's an option best left to people pursuing academics. But towards the end (point no 5) you advise to implement machine learning algorithms…How can that be achieved without knowing maths behind the algorithms.

PRINCE RAJ · May 15, 2019 at 5:44 am

can i learn deep learning before machine learning.
i have the basic idea if AI.

Techie ViN · May 15, 2019 at 9:52 am

Awesome Tips.. Really Relatable.. Thanks.

SAHIL ROHILLA · May 16, 2019 at 5:51 pm

I really like your videos man!

Pranav Patil · May 17, 2019 at 1:45 pm

How about datacamp?

Dev D · May 17, 2019 at 5:21 pm

Hey Gaurav!! I am just a beginner in the coding and stuff and have just studied python programming and I am planning to learn machine for which I have sorted out some things , which may be or may not be right . It would be a great help if you would tell me what to do , as just about complete me first year as a engineer .
So I have found these things which I should be studying for machine learning that is :
1) Pandas
2) Mathplotlib
4) Scikit learn

And would-be doing this on anaconda (jupyter notebook ).
I just heard up or just like a verification if I am going in the right direction, from people like you as you know at colleges they don't know much out of the course .
So I hope I would find my answers .

ravindra pawar · May 18, 2019 at 10:13 am

Hi Guarav,

How are you doing, I liked your video on machine learning as it is short and to the point.

I wanted ask you some questions on machine learning before that just giving you brief about me.

I am Ravindra Pawar working TCS from last 11 years in banking domain non technical. I have experience in cash management compliance, Trade finance, reconciliation and treasury also worked abroad for banking transition in commercial Banking and then my interest stared in machine learning.

I want to learn PEGA/PRPC certification i.e. CSA/CSSA and Blockchain. Hence wanted to ask you without having any technical background it ok to go head for this.

world peace · May 18, 2019 at 12:27 pm

Slow down man. You have a killer accent. I can only understand half what you were trying to explain.

Nikhil Salwe · May 18, 2019 at 1:53 pm

hello nice artical. I have one question my background with technical skills is Node.js, React, Angular can is there any course available with this technology or to learn AI or machine we need python only.

Thirukumaran PP · May 21, 2019 at 6:16 am

AppliedAIcourse check this course bro….am learning there

GAURAV ARYA · May 21, 2019 at 9:40 pm

Hello Gaurav, I have been watching your videos for the past 5 months and in each video, I get to learn a lot. So thank you very much for making informative videos. And there is one thing I want to ask, It's been 1 year since I graduated from University. I have done B.Tech in Computer Science Branch but I have less than 6 CGPA and I have been on a job hunt after graduation but haven't even got any yet. So, is there any chance for me to get a job as a software developer or should I go for other options? Please give me some advice.

nirmites CodingClub · May 30, 2019 at 6:16 pm


AnkytG · July 24, 2019 at 9:37 am

Thanks for the coupon code GS !!!!

Soham Talukdar · August 5, 2019 at 9:47 pm

Excellent points you mentioned. It will really help the community who wants to get into machine learning as a beginner.

Haseeb Ahmed Khan · August 14, 2019 at 7:19 am

Hi !
I'm a UG student in Electrical & Electronics Engineering currently in my final year, I don't know much about programming and i'm learning python and other ML courses from online.Can you recommend me or prepare a video of how to switch into ML from rather than a software background!

Afroza Sultana · November 11, 2019 at 6:02 am

I found your tutorials very helpful. It would be even better if you could speak a bit slowly πŸ™‚ Thank you very much!

Amit Shah · December 28, 2019 at 2:54 pm

@Gaurav Sen – Great advice. AI is the most common predicted trend as the future of software development in 2020 and going forward. My question is
– What kind of work/jobs would we get when we currently as software engineers adopt AI skills? Are these kind of jobs already present in the Indian market?

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