One word: https://www.coursera.org/learn/machine-learning
How much it costs exactly ?
Ask HN: How can a front-end developer dive into machine learning?
81–90 of 154 posts
Re: Ask HN: How can a front-end developer dive into machine learning?
#82Related question: If I only had an MIS undergrad degree (some 200 level stats and no other math) and wanted to get into machine learning what kind of math courses would I need to pick up to become proficient?
Re: Ask HN: How can a front-end developer dive into machine learning?
#83Related question: If I only had an MIS undergrad degree (some 200 level stats and no other math) and wanted to get into machine learning what kind of math courses would I need to pick up to become proficient?
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Re: Ask HN: How can a front-end developer dive into machine learning?
#84Related question: If I only had an MIS undergrad degree (some 200 level stats and no other math) and wanted to get into machine learning what kind of math courses would I need to pick up to become proficient?
> what kind of math courses would I need to pick up to become proficient?
look ML courses and their prereqs.
Re: Ask HN: How can a front-end developer dive into machine learning?
#85I am a long time developer who is trying to move into data science / ML. What I've found after taking off for 12 months of self-study, is that it quickly dissolves into you must know math . As far as I can tell, its take a problem, map it into a vector space, then use the full power of mathematical analysis on it . There is a huge push by large companies to make AI as a service though, and for that, you only really n…
For sure work through a linear algebra book, a stats book and some probability theory. Some basic calculus as well. Work through all of the simple examples. Just like programming..
That level of math helps to model the problem domain. The part of modeling the problem is to see that everything in ML is a graph. So you can look at it from that point of view as well, at least computational wise. Mapping the math to the graph is the heart of it all.
Re: Ask HN: How can a front-end developer dive into machine learning?
#86Hey honest question. I have worked with ai and nlp guys. How i have seen this works out: there is a problem x. They get the best most recent respected research on the problem x. They implement it most of the time it's on (github). If it doesn't solve the problem at hand they shrug their shoulders and say something like "it is the standford nlp parser can't do better than that!" the concept "getting into ai" - I am co…
Stanford parser is very good for preprocessing data. Things like part of speech tagging, named entity recognition, and dependency parsing. If you want to do something fun and interesting with your data, you will probably need to implement it yourself. Note, there are lots of other go-to tools nowadays besides the Stanford parser. Things like GloVe embeddings, open source translation systems (harvardseq2seq, open sour…
The big gains now are taking these pre-processing tools in speech, vision, NLP etc and using that as input to a NN for some problem domain. Every one of these is a startup.
Re: Ask HN: How can a front-end developer dive into machine learning?
#87it depends if you want to be a data engineer (lots of need for that), software engineer that developers code for data scientists (Software Engineer: Machine Learner - also lots of demand), or a data scientist. the latter, 'might' be a challenge. I started looking into linkedin profiles of data scientists of top tech companies after I realized there were more wharton mba's as data scientists than there where people wh…
Isn't there a joke that a data scientist is a statistician who knows SQL?
It's also weird when we say collate big data and data science.
Any statistician worth their salt can do inference in limited/noisy data sets.
Re: Ask HN: How can a front-end developer dive into machine learning?
#88Earlier quoted context omitted.
Well the article builds around a very superficial view of ML. If you want to do simple recommendation systems or spam filters than O.k. Those are solved problems, hence commoditized. If you want to build novel things, you really need academic-grade ML. If you want another argument, I came from working in VC and startups, and they think they understand ML. Boy, they really don't. They are like kids pretending to play…
Different approaches suit different people and PHD is a relatively specialized route. It's good to have people targeting similar goals with different approaches. For an anecdote, I recall hearing one of the Kaggle founders mention that many of their bounties are won by non-statisticians/ML-ists. Producing novel (in the academic sense) stuff is unlikely outside of an academic setting, but producing products or solving…
I think if the problem is figuring out an ML solution to an already existing large dataset (as in the case of Kaggle and big companies), you do not need an advanced education. However, if you are doing a start-up one needs to answer questions like when should I stop collecting data, when should I give up trying this algorithm, when should I conclude this problem is impossible in its current form etc. These questions require crazy amount of experience of solving novel problems. During your PhD, you try to solve many novel problems and it makes you an expert to answer these questions. I also think you need an advisor/mentor to develop these skills. This is the real knowledge you can learn in PhD and that's why they are valuable and hard to replace
Re: Ask HN: How can a front-end developer dive into machine learning?
#89Earlier quoted context omitted.
u mad, bro?
The same thing happened in the 90's, my coworker's sister got a "Certificate in HTML" and promptly found a job for $80k in 1998. These people wash out, I've been burned enough times by bootcamp grads that I won't hire them anymore
You are over generalizing.
I am a bootcamp grad who specialized in undergrad in electrical engineering. I worked for a few years as a research for the one of the top tech universities in the country; I have found that I have a stronger math and physics background than many CS grads. However, many times when doing something I have been stopped by saying "wait aren't you a bootcamp grad? can you even understand this?"
I'm not alone; my bootcamp had plenty of STEM majors. One of colleagues was a biomedical engineer and worked in a research lab and now works in the front end at a top firm in SF. Another was a math major at an Ivy before working full stack. The top guy at my bootcamp went to Berkeley in Biochem and was way way smarter than me.
So stop generalizing. I understand that they are unaccredited institution so you get a wide variance of talent but you can't shit on everyone.
To be honest, your issues probably in how you screen talent. My current company has found success in hiring bootcamp and top schools in the area (Berkeley, Stanford).
Re: Ask HN: How can a front-end developer dive into machine learning?
#90I am a long time developer who is trying to move into data science / ML. What I've found after taking off for 12 months of self-study, is that it quickly dissolves into you must know math . As far as I can tell, its take a problem, map it into a vector space, then use the full power of mathematical analysis on it . There is a huge push by large companies to make AI as a service though, and for that, you only really n…
> Sure I have a new found love for math, but I'm not going to be accepted as a mathematician ever without the rigor of a formal education
I think there are two separate things here:
1. Being a research mathematician requires a degree of expertise which is easier to come by with formal education.
2. Knowing how to use APIs and make correct distributional assumptions; despite the bullshit fed by our industry, it is not easy or non trivial to design a completely idiot proof API. So having know-how of how the math works under the hood is helpful even if you are going to just use the API.