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Ask HN: How to Seriously Start with Machine Learning and AI

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Re: Ask HN: How to Seriously Start with Machine Learning and AI

#61

Post by BucketSort »

Byzantine_BG wrote: post #56
BucketSort wrote: post #30

I'm very adamant that if you really want to be an AI researcher, it starts with the mathematics. Multi-variable calculus, linear algebra,discrete math, probability and statistics are key. The classic books and courses others have suggested are excellent starting points. I'll also say something here that isn't established, so I may take some heat. I believe there are two main paths in AI that will eventually converge…

One day 40 years after I graduated I "got" linear algebra. The eigenvectors of the inverse of the covariance matrix... Squeeze and twist it into a hypersphere! Mahalabobis distance is generalized z-score! Oh!

That's the ticket. It's all about building that intuition so you can be creative with mathematics. Linear algebra in particular is an area that continues to teach me more over the years.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#62

Post by makeset »

> I'm a third-year Computer Science student

Make sure you take, as soon as possible, all the AI & ML courses your department offers. If prerequisites are holding you back, try to negotiate or audit. (Some of my key insights date back to graduate-level AI classes they humored me to sit in on when I was a freshman.)

MOOCs are great for people who don't have that option, but you have the opportunity to ask questions, get course credit for your work, bolster your GPA, show it on your transcript, network with classmates, etc.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#63

Post by neel8986 »

emurillo510 wrote: post #41
neel8986 wrote: post #11

This is kind of a masters degree course i created for myself to get knowledge of Machine Learning from bottoms up First, you need a strong mathematical base. Otherwise, you can copy paste an algorithm or use an API but you will not get any idea of what is happening inside Following concepts are very essential 1) Linear Algebra (MIT https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra... ) 2) Probability (Harv…

hey neel8986, I know linear algebra is very important for large scale calculations. But how much calculus and statistics do you need for ML? Also, if you can touch what applications of calculus and statistics are used in ML that would be awesome :]. THANKS!

Regarding calculus, I think basic multivariable calculus can be enough for starting. If you need a refresher you can look for (https://ocw.mit.edu/courses/mathematics/18-02sc-multivariabl...)

Also the basic idea of chain rule is important for deep learning.

Regarding statistics, I already mentioned the probability course which describes most of the important statistics concept you need. Also, some idea of Hypothesis testing can be helpful

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#64

Post by enraged_camel »

enraged_camel wrote: post #20
atg_abhishek wrote: post #9

I'm surprised that no one has yet mentioned Andrew Ng's Machine Learning course on Coursera and to go a bit deeper, his deep learning specialization on Coursera as well. Along with the programming assignments it's a solid way to get your feet wet. And definitely second the suggestion of the fast.ai courses as well

I took this course. Andrew is a great teacher. However, I wish he worked on his public speaking a bit. He has certain speech patterns, like starting sentences with "it turns out..." and after a while it becomes extremely irritating, at least to me. Fantastic course though.

Lol, apparently we aren’t allowed to criticize people HN likes.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#65

Post by jrjames83 »

I would recommend working on as many Kaggle competitions as you can. Try your best to understand manipulating data quickly and efficiently (use Python). Using the correct algorithm is typically trivial and a solved problem for most typical business issues (classification of text, imagery or audio data). At first you'll have to look at other people's code and copy/paste/edit/learn/iterate. Also, don't underestimate the complexity of creating good training, validation and potentially test sets.

95% of your time will be spent massaging data. People say it so often, it may sound ridiculous, but I promise you, it's not. This skill is also readily transferrable to other domains.

I would start with classifying text using sklearn and Facebook's Fasttext.

Then try the dogs/cats image classification challenge and get familiar with Keras and its utilities. I created a few hours of content around recognizing Bill Gates or Jeff Bezos, then trying to recognize 2 types of dog breeds. I outline the challenges of creating "good" training and validation sets.

https://www.youtube.com/watch?v=O3hffX-jC98&list=PLImyDqSBQb...

For every hour you spend looking at some equations, you missed an hour expanding your skill-set to manipulate and get data into a format which can be fed into well understood and maintained algorithms. Once you feel like you get produce results, go back and think about the underlying mechanics. My 2 cents from experience.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#66

Post by vaibkv »

RosanaAnaDana wrote: post #35

I'm probably the worst example of how to get into this field of work, but since I do actually work on developing and applying ML algorithms every day, I think my case might be relevant. Firstly, my background is not in mathematics or computer science what-so-ever; I'm a classically trained botanist who started came at the issue of programming, computer science, and ML from a perspective of "I've got questions I want…

This is absolutely, hands-down best advice. I would definitely second this. I have done ML and Data Science projects on and off at my workplace and I definitely think I know much more than folks who are simply doing lectures, courses, etc. I think working on a problem is actually the only good way to learn just about anything when it comes to Computer Science and Data Science, in general. I would suggest the OP to pick a topic of interest, define a problem statement and work on getting results there. OP needs projects to work on.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#67

Post by vaibkv »

atg_abhishek wrote: post #9

I'm surprised that no one has yet mentioned Andrew Ng's Machine Learning course on Coursera and to go a bit deeper, his deep learning specialization on Coursera as well. Along with the programming assignments it's a solid way to get your feet wet. And definitely second the suggestion of the fast.ai courses as well

Does not matter the number of courses one does. Knowing when to apply what and practical know-how only comes when you do real world projects on your own. In OP's case, it might very well be building NLP projects, doing image classification (insects and plants, maybe?), making one's own recommender system to suggest movies - but unlike Netflix this will also recommend dissimilar ones. Writing or improving on research papers is another way to go about it.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#68

Post by jamez1 »

Make sure you load up on mathematics, in both pure and applied. Try to find work where you'll either be immersed in statistical models or have the freedom to experiment with them.

Capital markets such as equities trading will probably be the best place to look for work experience.

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#69

Post by tinymollusk »

ImNotBeingADick wrote: post #51
tinymollusk wrote: post #37

In October, I quit my job to live on savings and work on AI/ML. I am not interested in developing novel AI approaches; my objective is to learn the application of machine learning to solve narrow problems. In light of that, I believe the technology to have progressed to where one can learn how to use existing libraries to solve specific problems. Lots of businesses have specific problems, and will pay me to solve the…

I've been doing Coursera and got done with Udacity but both are just too philosophical. (I'll probably cruse the deep learning class too.) Does FAST.AI get into the grit of actually doing or is it more philosophical?

Very focused on getting shit done, while trying to help you build appropriate mental models to what's going on. Towards the end of the course, some more theory.

Multiple times, the prof said things like "the theory says this shouldn't work, but it does, so we use it." (Thinking about his perspective on the practical reality surrounding the "curse of dimensionality" (i.e. that it's not a curse)

Re: Ask HN: How to Seriously Start with Machine Learning and AI

#70

Post by abhgh »

BucketSort wrote: post #30

I'm very adamant that if you really want to be an AI researcher, it starts with the mathematics. Multi-variable calculus, linear algebra,discrete math, probability and statistics are key. The classic books and courses others have suggested are excellent starting points. I'll also say something here that isn't established, so I may take some heat. I believe there are two main paths in AI that will eventually converge…

I completely agree with you on knowing the math part. I am kind of emphatic about it too when doling out advice. Without that, getting good results just becomes a blind exercise in tweaking parameters. With that, you can really troubleshoot your models, and know what model(s) to try next; the path to optimality is somewhat meaningful and reasonable.
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