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The AI Entrepreneurship thread. Code AI? Interested in AI? Data Science? Machine Learning?

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ChrisV

ChrisV

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AI is certainly the buzzword these days. I invested in a startup AI company early this year -- six months later, they were able to recapitalize at 25x the valuation with institutional money and had VCs fighting to get in the raise (luckily I got my money in before they realized they didn't need it :).

I have a feeling that we're going to be talking about a bubble in the AI space in a couple years...
It depends on how you use it. It's almost definitely going to be both a boon as well as a bubble.

It's going to be like the dot com era. There are going to be legitimate uses for it, and there's going to be the crackpots who just want to create MeToo crap.

We're already seeing tons of legitimate uses for it. Netflix Recommendations, Google searches. Self Driving cars. Every major tech company uses some amount of AI.

It's how it always goes with these tech advances. There's the wheat, and the chaff.
 

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JScott

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It depends on how you use it. It's almost definitely going to be both a boon as well as a bubble.

It's going to be like the dot com era. There are going to be legitimate uses for it, and there's going to be the crackpots who just want to create MeToo crap.

We're already seeing tons of legitimate uses for it. Netflix Recommendations, Google searches. Self Driving cars. Every major tech company uses some amount of AI.

It's how it always goes with these tech advances. There's the wheat, and the chaff.
I think you're misinterpreting what I mean by bubble. I wasn't implying that the industry isn't viable. Just like there was a bubble in Internet technology in the late-90s (rightfully so), but that didn't mean that Internet tech wasn't a viable industry -- it's likely one of the greatest economy drivers in the history of the world.

But, with Internet tech, the fact that there was an over-concentration of investment without sufficient income generation meant that valuations grew WAY out of whack, and the market cap had to realize a big correction before growth continued.

We'll see the same thing in AI (in my opinion) -- valuations will be overblown, and in a few years, after a lot of buyouts, consolidations and IPOs, we'll see a correction in market cap. And then we'll see more rationale growth for the subsequent decades.

I think AI will move the needle on the economy over the next couple decades, but it won't be linear growth. That's what I meant by a bubble...
 
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ChrisV

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I think you're misinterpreting what I mean by bubble. I wasn't implying that the industry isn't viable.
Oh gotcha. I thought you were leaning toward meaning a speculative bubble.

But yes I agree with the oval sentiment. There will be a legitimate bubble, and a speculative bubble.

There will probably be Tesla, and then companies who want to put AI technology in your shoes (actually maybe that isn't a bad idea.. it would make a cool pedometer, but you get my point.)

We'll see the same thing in AI (in my opinion) -- valuations will be overblown, and in a few years, after a lot of buyouts, consolidations and IPOs, we'll see a correction in market cap. And then we'll see more rationale growth for the subsequent decades.
Yep. Everyone's gonna want to get on board, whether their idea is legitimate or not. The legit ones will stick, and the nutty ones will burst. And I think AI will act as a catalyst for other innovations (medical, scientific, agriculture.)

Definitely going to be interesting to watch.
 

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I remember watching an interview with a scientist from Elon Musk's Neuralink saying that they were making an implant onto the brain where it's like The Matrix in that a person can download a language.

They succeeded doing it with rats. An implant was attached to the brain and it tracked the rat's brainwaves.

Scarier and cool at the same time.

Sci-Fi is always becoming reality.

Communicator in 1960's Star Trek and now we have tiny cell phones.
 
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ChrisV

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Just wanted to post some of my favorite resources for anyone who wants to learn,

This guy (quite ironically) used Data Science to rank every Data Science course on the net


But these are hands down my favorite courses on the net:


AnalyticsVidhya is hands down my favorite Data Science blog on the net.

Also for anyone interested, Harvard offers a real good soup-to-nuts Data Science program on their site. You can do it completely online

 
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ChrisV

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Also, I mainly do Data Science, but lately I've wanted to expand my skillset to include more Machine Learning applications.

Is anyone interested in learning Machine Learning?

I was debating going for AnalyticsVidhya's "AI Blackbelt Masters" program. I've had amazing results from their courses in the past (I find them to be the most comprehensive.)

If anyone want to split it, message me or post here. The cost is ~$625, but I looked up the reviews and it seems well worth it. Plus all their other products I've used in the past have been ultra high quality. I don't plan on using all the courses in the bundle, so if anyone wanted to split the cost, that would save us a few bucks. The amount of people they take on for it is limited since you get free coaching with it, but I preregistered a bit back.

If anyone is potentially interested, let me know. It could be a really cool set of classes.
 

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How profficient in coding do you need to be to start doing things like AI, ML or Data Science?
I have no prior coding experience (just some html and css), and I recently started learning python (halfway through Automate the Boring Stuff). I want to know what's a reasonable timeframe to start doing more advanced stuff like AI or ML. Is even python a good language for this?
 

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Won't entrepreneurs be able to hire coders to write the AI while they design it for the market they've found that needs it?
 
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ChrisV

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How profficient in coding do you need to be to start doing things like AI, ML or Data Science?
I have no prior coding experience (just some html and css), and I recently started learning python (halfway through Automate the Boring Stuff). I want to know what's a reasonable timeframe to start doing more advanced stuff like AI or ML. Is even python a good language for this?
This is a tough question because I had somewhat of a background in stats before I started. I mean you can probably run some relatively simple analyses in 6 months.

Won't entrepreneurs be able to hire coders to write the AI while they design it for the market they've found that needs it?
Sure, but even if you have people working for you you should know about ML. Zuckerburg knows how to code, and I don't know if Zuckerburg would be Zuckerburg if Zuckerburg didn't know how to Zuck.
 
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Zenoviy Kovtun

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Plus me personally.. I'm a 'get your hands dirty digging through data' type guy. It's a flow state for me.
Hey Chris, thanks for sharing all this valuable info. What's your take on data sci vs finance? I currently work in real estate banking but am torn by the strong need for data sci/analytics in the market. Looking to maximize my job income as I work on a fastlane product in a separate field. What's your opinion on pursuing data sci vs finance? I intended to make real estate my career, (while working on side biz) but the need for data sci seems so strong. I dont usually believe in followings one's passion(over mkt demand), so still on the fence. My goal so far is to pick up using R/Python since both fields can sometimes mesh. Any sort of feedback would be appreciated!
 

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ChrisV

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Hey Chris, thanks for sharing all this valuable info. What's your take on data sci vs finance? I currently work in real estate banking but am torn by the strong need for data sci/analytics in the market. Looking to maximize my job income as I work on a fastlane product in a separate field. What's your opinion on pursuing data sci vs finance? I intended to make real estate my career, (while working on side biz) but the need for data sci seems so strong. I dont usually believe in followings one's passion(over mkt demand), so still on the fence. My goal so far is to pick up using R/Python since both fields can sometimes mesh. Any sort of feedback would be appreciated!
1562673768823.png
  1. What are you good at
  2. What do you enjoy doing
  3. What does the world need
  4. What can you get paid for
We know that DS is something the world needs and is something you can get paid for... but what do you think you'll be better at? And which would you enjoy more?

I wouldn't just go do data just because it's a trend right now.. i'd think about what you're also suited for. And there's no reason you can't use Data Analytics in finance. Data can be applied to everything. I see no reason why you can't do both.
 

ZF Lee

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Hey Chris, thanks for sharing all this valuable info. What's your take on data sci vs finance? I currently work in real estate banking but am torn by the strong need for data sci/analytics in the market. Looking to maximize my job income as I work on a fastlane product in a separate field. What's your opinion on pursuing data sci vs finance? I intended to make real estate my career, (while working on side biz) but the need for data sci seems so strong. I dont usually believe in followings one's passion(over mkt demand), so still on the fence. My goal so far is to pick up using R/Python since both fields can sometimes mesh. Any sort of feedback would be appreciated!
(I forgot whether I included this nitbit into the lecture notes I sent you! @ChrisV)

Rob Hyndman popped by at my university the other day, and he described being a data scientists like this:
'Being a data scientist (or doing data science) is being more skilled in programming than a statistician, and being more skilled in statistics than a programmer.'

So, I feel the heart of data science is statistics, while programming for data science itself is the tool for the means to an end.

And if you look at the fundamentals of finance, such as standard deviations for risk and volatility, statistics is heavily linked to finance.

Me thinks some knowledge in just using Excel will just be fine.
I take finance units in university presently, and they don't need me to do R programming.

And just remember that any data analytics method can only be as good as its dataset.

If the dataset is too F*cked to be cleaned up...well, rubbish in, rubbish out.
This goes back to how the folks collected the data in the first place.
 
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ChrisV

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'Being a data scientist (or doing data science) is being more skilled in programming than a statistician, and being more skilled in statistics than a programmer.'
Yes. Data Science is the illegitimate love child of Statistics and Programming.

It's basically like using a programming language as a big, fancy graphing calculator. Except the analytics you'll run are thousands of times more complex and millions times if you're doing Machine Learning.
 

Lihan

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Had to make an account since I'm a data scientist trying to get on that sweet fastlane.

Anyone want to throw around needs that data science can address? With my experience (NYU Data Science MSc and Air Force Research contractor for my day job) I'm more focused on evaluating good ideas following CENTS than worrying about execution (in terms of product dev).

Fastlane projects tend to be smaller in scale and less innovative than full fledge startups I'm exposed to in DS/ML, which is perfect. I think a lot of startups are too utopian in mindset even if they follow the Lean methodology.

In one of the gold threads Monthly Reoccuring Revenue was brought up, so I think I'll start on that as proposing 'give me your org needs and data, I give you data solution + re-occuring maintainence plan', and try to stack a couple of those. Thoughts for people in the DS+fastlane life?

Be glad to answer literally any ML questions! Confident I can give a good answer or point to better resources. My writing about tools used for the air force contract.
 
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ChrisV

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Anyone want to throw around needs that data science can address?
This is a hard question to answer because there are so many answers. I think the right data can optimize almost anything. It's basically like 'sciencifying' our everyday decision making. Traditionally before the 1900's the world relied on gut feelings to make decisions, but science uses measurements that are empirical and objective. This scientific approach revolutionized many fields (medicine especially,) and I think you're just starting to see the whole world go through that transition because of the amount of data we have. So now we can make decisions based off objective numbers rather than our flawed feelings.

Scroll up to see my Moneyball example.

Now people want to use that approach everywhere


But AI is the next level of that. It allows for much more complex computations, and is starting to make the Moneyball approach seem archaic.

Thoughts for people in the DS+fastlane life?
You can help businesses build dashboards for their business. There's one guy on here who dod something similar:


But there are so many things you can do with AI / ML / DS.
 
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ChrisV

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Thoughts for people in the DS+fastlane life?
Stanford professor Andrew Ng is probably the leading name in AI. You can hear some of his thoughts on this here.

His talk is entitled "Artificial Intelligence is the New Electricity," which is a bold claim, but I think accurate.

 

Lihan

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Another thought I've had is scrape [ Google My Business ] business listings (the business info you see on Google maps) and build a model that can 1) predict your future ratings by looking at your biz profile and 2) give you improvement pointers based on what successful businesses similar to your profile are doing.
 
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ChrisV

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I'm also compiling a list of my favorite resources in a separate thread. All the resources so far are free except Harvard's Data Science certification.

1567462709750.png

You don't even really need that though. I just got it because I thought it would be nice to add to a resume, which I havent even needed. In this field as long as you're capable and can do quality work, people will hire you. The formal certifications, etc. don't matter so much. In my opinion, you're better off showing off some cool projects of Github or whatever.

But anyway, these are some of my favorite resources:

 

Lihan

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Another thought I've had is scrape [ Google My Business ] business listings (the business info you see on Google maps) and build a model that can 1) predict your future ratings by looking at your biz profile and 2) give you improvement pointers based on what successful businesses similar to your profile are doing.
I made a landing page following this idea, had to commit an afternoon of research about landing pages, haha (first time!). I'm sure the veterans here has advice that can 1billionx the conversion rate on this. (which would be appreciated for my own learning)

You don't even really need that though. I just got it because I thought it would be nice to add to a resume, which I havent even needed. In this field as long as you're capable and can do quality work, people will hire you. The formal certifications, etc. don't matter so much. In my opinion, you're better off showing off some cool projects of Github or whatever.
That's been my experience as well. I think a lot of writing from other professionals have covered creating a great resume for a data scientist job or interviewing for FANG. Not a lot has been done on completing an interesting project AND commercializing it, all with 1 or 2 people. More importantly I feel a lot of data science got held up by corporate 9-5s when there's a ton of value to be unleashed if, say, everyone tried their own ventures. Maybe there's opportunity to experiment in-house.
 
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ZF Lee

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In my opinion, you're better off showing off some cool projects of Github or whatever.
You can also check out Kaggle.


It hosts data competitions with datasets all many genres...product logistics, crime rates, google traffic...

You can hop onto a competition without any charge, if I am not mistaken, and get the dataset. But you may have to clean up data before you begin working though.

Folks can also read the documentation on past winners, and how they got the best method.
 

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How profficient in coding do you need to be to start doing things like AI, ML or Data Science?
I have no prior coding experience (just some html and css), and I recently started learning python (halfway through Automate the Boring Stuff). I want to know what's a reasonable timeframe to start doing more advanced stuff like AI or ML. Is even python a good language for this?
Yes, Python is arguably the best language for AI/ML. If you are interested in it I would stick with Python.

You are on the right track from AtBS, I would finish that then pick up a beginner Python AI/ML book and get your feet wet. Or take a course online.
 
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ChrisV

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I think that data really has it's place in nearly anything. I think you'd be hard-pressed to find any industry that won't be transformed by data and AI.

“That which is measured, improves” – quote attributed to Karl Pearson

The fact that we have data on everything is just like having a speedometer. We can now measure progress and know if what we're doing is working.

Moneyball 2.0:

View: https://www.youtube.com/watch?v=9rOKGKhQe8U
 

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Stanford professor Andrew Ng is probably the leading name in AI. You can hear some of his thoughts on this here.

His talk is entitled "Artificial Intelligence is the New Electricity," which is a bold claim, but I think accurate.

The Deep Learning Coursera Specialization I mentioned earlier is taught by Andrew Ng.
 

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The Deep Learning Coursera Specialization I mentioned earlier is taught by Andrew Ng.
I ended up doing it. I'm half way through. It's a good introduction, although it looks like I'd need a real project to work on later.
 

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How profficient in coding do you need to be to start doing things like AI, ML or Data Science?
I have no prior coding experience (just some html and css), and I recently started learning python (halfway through Automate the Boring Stuff). I want to know what's a reasonable timeframe to start doing more advanced stuff like AI or ML. Is even python a good language for this?
Python is THE language for AI / Deep Learning, so you're on the right track.

What are your goals? I was just talking with @ChrisV about the material over at fast.ai

If you want to get started quickly and just start doing deep learning, then check it out. It's free, highly regarded, and will get you rocking and rolling on day 1.

From there, reassess what you want to do. If you just want to use off the shelf stuff to start solving problems, you're good to go. If you want to go deeper and learn what makes this stuff tick, then you're going to need to learn a fair amount of math.
 

Michaellyam

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Today AI has reached almost every sector — be it our homes or office — AI enabled gadgets are everywhere. Alexa, Siri, self-driven cars are just some of the examples of how machines can be taught and perform the functions that a human mind can perform. This is the simplest definition of machine learning, that enables computers to network and discover set patterns that are found in huge data. And as organizations world over embrace AI, there has been a surge in the demand for AI Professionals.

I am an AI enthusiast -love to learn and embrace technologies that changing our lives.
 
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ChrisV

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Python is THE language for AI / Deep Learning, so you're on the right track.

What are your goals? I was just talking with @ChrisV about the material over at fast.ai

If you want to get started quickly and just start doing deep learning, then check it out. It's free, highly regarded, and will get you rocking and rolling on day 1.

From there, reassess what you want to do. If you just want to use off the shelf stuff to start solving problems, you're good to go. If you want to go deeper and learn what makes this stuff tick, then you're going to need to learn a fair amount of math.
Yea, I like fast.ai's approach. As long as you have a year coding experience. they just get you up and rocking within the first lesson. You'll have run a pretty decent ML algorithm within the first two hours.

I try to take a pareto (80/20) approach to learning. Skip the fundamentals, learn the 20% most important things you'll need for day-to-day operation, then figure out the fundamentals afterwards.

In reality, you don't need to know how a car works to drive. But like @lowtek said if you want to push the envelope, that's when you want to learn how a car works.

Today AI has reached almost every sector — be it our homes or office — AI enabled gadgets are everywhere. Alexa, Siri, self-driven cars are just some of the examples of how machines can be taught and perform the functions that a human mind can perform. This is the simplest definition of machine learning, that enables computers to network and discover set patterns that are found in huge data. And as organizations world over embrace AI, there has been a surge in the demand for AI Professionals.

I am an AI enthusiast -love to learn and embrace technologies that changing our lives.
Are you a professional writer? I thought there was going to be a sales pitch at the end but i just got curve balled lol
 

PedroG

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I ended up doing it. I'm half way through. It's a good introduction, although it looks like I'd need a real project to work on later.
Yup, I'm starting the last course, "Sequence Models" this week. I finished the Convolutional Networks one last week.

Once I'm done with everything I got a project I wanna work on where I can incorporate a lot of what I've learned.

The Convolutional course was great. You get to see how art can be generated by combining the content of one image and the style of another. Awesome stuff. And once you understand how the process works, it's actually quite simple and you can imagine how other things can also be generated, like Music, etc. The possibilites are freaking endless with these algorithms.
 

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