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

ZF Lee

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iam very interested in this topic, here are my questions for you AI pros out there:

1. What business in AI would be profitable if i start today in 1-3 yrs?
2. I guess coding is a big part, so i cant do it alone, how would you solve that problem if i want to start a AI business with low budget.
3. What fields are most affected in the next 5 years by AI! please give me some answers i cant google haha

Cheers
Today in my forecasting lecture, my professor said,
'I don't think AI will totally replace the jobs. But what is certain is that it can automate certain components of the job.'

He explained that because at that moment, we were looking at R programming codes to use for ARIMA, an approach that needs us to look for white noise, that tells us whether the data is legit or not.

We can automate the creation of the graphs, but we still had to read it and its benchmark indicators to tell us a story.

So, 1-3 years is a short time.

Me thinks that to pick the lower hanging fruit, you have to see:

1. which job component can be directly automated- maybe its currently undergoing automation already, but still has room for expansion

2.which data that the AI (or stats software, for that matter) can pick up easily, or can be coded in smoother, with faster data cleaning and pre-processing.

I think you'd have to consider what most programmers of AI can simply do, on average, since they will still be doing some work.

3. Type of deliverables. If your ultimate product is info/data based (e.g. AI-based market report), then you can quickly market that solution. But if you have to use the AI results to transfer info to let's say, for a physical factory mechanism to work, that of course, it takes some costs and time for implementing.

IMO, probably accounting (especially costing and logistics) and finance would be most affected. Much of it is info/data based, stuff you can transfer quickly on the cloud as deliverables, and the observations values are mostly dollar-sign....

Fundamentals like costs, optimization, risk and volatility, are inherent in basic statistics behind AI, and anything related to the transaction of money is directly impacted.

The two fields are already affected, but somehow we are still stuck with archaic methods like banking checks...the final nails in the 'coffin' are yet to be delivered.

IMO, I think there's room for AI, or software tools, that:

1. Not only LINKS psychological and demographic info with financial data for regressions, forecasting, etc.

2. but also ASSESSES and UPDATES the models consistently, as there is never one perfect model-especially the psycho and demograph part.

On a side note...

There was an earlier argument in another thread between James Fend and JScott as to whether data methods trump human emotions in telling what comes in the future, and vice versa.

Both have good points, but I think if we can throw things up into an equation for analytics, it might be good to take the error term, and see if we can get some constant or a function to capture some of that error in terms of psycho/demographics.

Of course, that so-called function or constant would be dynamic, depending on the parameters of choice, but that's where automation can come in.

As for roping in help, you can try looking into the open-source model.
I found it interesting that the R program environment is almost entirely open-source generated, as well as its packages.

I have mentioned earlier that there is a website on this thread called Kaggle, where folks join contests to come up with the best predictive models for a problem.

And while there are cash prizes, somehow, reading their immense documentations feels as if the folks who join it are mostly there to do their passion for data, rather than for the cash alone.

Is it possible to call on such people, network with them? Maybe.
 
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Roli

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I bought the course you recommended, Analytics Vidhya. Why do they use Jupyter? I've never used an IDE that needed to be accessed from the terminal, so I found it a little strange.

Can you tell me a little about this course please. What is it good for? What level do you have to be at? etc.

Thanks.
 

ChrisV

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Can you tell me a little about this course please. What is it good for? What level do you have to be at? etc.

Thanks.
So the course I'm doing now is this:

Which I recommend.

His pitch is that he gets you getting world class ML results in days or weeks, not months. You code your first Neural Network in the first lesson. It's essentially learning how to drive without understanding exactly how the car works. Then he goes back later in the course and shows some of the mechanics. He says about a year of python is recommended, which I'd say is about accurate. If you don't have that, I'm sure you can do it; it will just be harder.
 

Strategery

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Can you tell me a little about this course please. What is it good for? What level do you have to be at? etc.

Thanks.
I bought the entry level course. There are no requirements for it. If you've ever done anything with DS then it's a little basic.
 
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ChrisV

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Roli

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So the course I'm doing now is this:

Which I recommend.

His pitch is that he gets you getting world class ML results in days or weeks, not months. You code your first Neural Network in the first lesson. It's essentially learning how to drive without understanding exactly how the car works. Then he goes back later in the course and shows some of the mechanics. He says about a year of python is recommended, which I'd say is about accurate. If you don't have that, I'm sure you can do it; it will just be harder.

Thanks for that. I have about a year's worth of Python maybe more, but I'm rusty...

The link you sent directs to five different links. I take it I should just click on the first one?

It's a bit confusing, that website needs a fastlane makeover! :cool:
 

ChrisV

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Roli

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I bought the entry level course. There are no requirements for it. If you've ever done anything with DS then it's a little basic.

The link Chris sent me said all the courses are free; are you talking about the same one?

Maybe it's because it's 5.30 a.m. or maybe because I'm a complete rube, but for the life of me I can't work out what DS is.
 

ChrisV

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The link Chris sent me said all the courses are free; are you talking about the same one?

Maybe it's because it's 5.30 a.m. or maybe because I'm a complete rube, but for the life of me I can't work out what DS is.
No there are two different ones I recommend... both are really good. fast.ai is the one I'm on now, but I love AnalyticsVidhya as well. When I recommended that course, it was before I realized there was a great free one... sorry @Strategery .. but AV is still great. AV really gets into real world applications for this stuff.
 
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Strategery

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No there are two different ones I recommend... both are really good. fast.ai is the one I'm on now, but I love AnalyticsVidhya as well. When I recommended that course, it was before I realized there was a great free one... sorry @Strategery .. but AV is still great. AV really gets into real world applications for this stuff.
Lol, no worries.
 

ChrisV

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So guys, here's a fun fact. Have you ever wondered why those CAPTCHA puzzles always contain driving-related images? Well it turns out you're actually teaching Self-Driving cars how to drive.

1568819641562.png

 
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ChrisV

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BlindSide

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Crazy thought I had: it’s estimated that every 50 minutes, someone is killed in alcohol-impaired accident. Could AI and technology be implemented into cars to sense an alcohol impaired driver?

Maybe it could prevent the car from being turned on? Or say it’s on the road and it senses driving habits that indicate an impaired driver, some type of ability for the car to pull over/get off at the nearest exit?

Food for thought for my crazy brain.. and the Elon Musks of the world. Just imagine: This is a $44B problem every year.
 

nitrousflame

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Could AI and technology be implemented into cars to sense an alcohol impaired driver?

This seems like a very temporary problem. E.g., why bother with testing the human when the AI will just drive the car itself?
 
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Kid

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Crazy thought I had: it’s estimated that every 50 minutes, someone is killed in alcohol-impaired accident. Could AI and technology be implemented into cars to sense an alcohol impaired driver?

Maybe it could prevent the car from being turned on? Or say it’s on the road and it senses driving habits that indicate an impaired driver, some type of ability for the car to pull over/get off at the nearest exit?

Food for thought for my crazy brain.. and the Elon Musks of the world. Just imagine: This is a $44B problem every year.

I heard that some travel coaches have that, not heard about it in personal cars.
 

BlindSide

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Just did a quick Google search, and apparently both Volvo and Nissan are in the process of implementing this technology.
Looks like the article on Nissan is from 2007.. curious as to what’s happened since then
 

BlindSide

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This seems like a very temporary problem. E.g., why bother with testing the human when the AI will just drive the car itself?
Yep, but here’s the thing - will they make the cars so that we can’t drive it no matter what? Maybe I don’t want AI to drive my car all the time?

So can drunk drivers manually turn it off? People make very poor decisions when they’re drunk, like maybe wanting to see how fast the car can go.
 
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ChrisV

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cha-ching

 

ChrisV

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So I have a new recommendation for anyone wanting to get into the world of analytics. This will apply more to Data Science than AI, but if you're looking to get into Data Science, I've changed my recommendation in that I highly recommend starting off with Tableau. I've actually been using it a lot myself lately, and I do some pretty hardcore statistics.

Even if you later decide to pick up a programming language, if you know Tableau you'll be 10 steps ahead of the game. It's a lot on your plate to learn programming and Data Science at the same time, and Tableau will make that transition more gradual.

Looking back I wish I would have done that. I spent months/years stressing myself out learning things the hard way, now I truly believe my life would have been much easier had I done that.

But that's not to say that Tableau is for beginners by any stretch of the imagination. It's amazing software made by very good statisticians, and has a lot of 'best practices' baked right into the software. A lot of industry professionals use it, and I've even found myself using it for certain tasks that are a pain in the neck to do at a command prompt.

This article is a great reference and actually a Tableau course (Data Science A-Z™) took their #1 spot in the Analysis:

Tableau's webside is also one of the best resources on the software as well:

If you want to take it to the next level, you'll probably want to learn a programming language, but Tableau is a great start, and a tool you'll probably always use if you learn it.
 
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S.Y.

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@ChrisV

Can you talk a bit more about the business aspect of running a data science company?

I think it would be valuable to have an idea of how can a one-man data science company works. What kind of projects are you tackling? what does the deliverable look like? How do you go about finding clients? etc....
 

ChrisV

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Yea.

I personally do a lot of work for academia (university research/social science) - mainly because that's what I like doing, but I also do work for businesses.

But I'm not always a one-man operation. I often outsource certain tasks, especially when they're big projects. Sometimes these projects can be pages and pages of code, or I'll need something that's completely outside of our skillset. When I need something done I can message someone in my network and pay them.

Deliverables are usually in the form of data visualizations as that's generally the best way to communicate your findings. Sometimes in the form of interactive visualizations.

I generally just find clients by word of mouth, or people just know what I do and ask. You make friends with someone while you're out and about, it turns out they own a company and shoot you an email about something they need help with. That happens a lot.

Sometimes people from the forum will even message me with stuff. Speaking gigs, whatever.

I'm also not afraid to do a little pro-bono work on causes I believe in. I do it just to help, but it ends up adding to your connections. I wrote a little bout that here


I may be able to do even better by advertising, but I just haven't needed to.
 

Martin.G

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This is really an interesting Thread. I have studied ML in college, and I was very interesting in the subject. All of my project for the course was related with finance, because I love finance.

I am wonder if there are anyone working right now, or in the past, in solutions related to AI/Machine Learning in the field of finances or business. Maybe in a SaaS. I am interested in create a business about that in the future

Also, in the last time I have recovered my interest in this field, so I have been doing the course of the YouTube channel sentdex. He has a course about Machine Learning with python, and for now it looks interesting. Also, he has another one about finance/investment but I don't try it yet. My next step is I take a look at the course that has been recommended here from Stanford in Coursera.
 
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Zubz

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For someone who doesn't know a thing but is intrested in AI, where to start?
 

Martin.G

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For someone who doesn't know a thing but is intrested in AI, where to start?

Do you know how to program?

If you don't, you can start learning Python, that's a programming language that you are probably going to use. There are others, of course, but in my opinion there are a lot of course and information on YouTube where they use it to teach. For example, the channel that I mention before.

Also, you can start reading the thread, there a re tons of course and recommendations here. Again, the YouTube channel that I mention earlier is a good start, you need to know the basic in python but then, you can learn more while you are watching the class. I like it because he starts from the basic aspect of ML. Also, he teaches how to use the libraries that are available, but also how to code the algorithms from scratch. I think is important too, because you see practically how they work and why the libraries are better because of their optimizations.

That's my two cents. I am not an expert and, from what I read here, there are very capable people around, maybe there have another advice.
 

Zubz

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Do you know how to program?

If you don't, you can start learning Python, that's a programming language that you are probably going to use. There are others, of course, but in my opinion there are a lot of course and information on YouTube where they use it to teach. For example, the channel that I mention before.

Also, you can start reading the thread, there a re tons of course and recommendations here. Again, the YouTube channel that I mention earlier is a good start, you need to know the basic in python but then, you can learn more while you are watching the class. I like it because he starts from the basic aspect of ML. Also, he teaches how to use the libraries that are available, but also how to code the algorithms from scratch. I think is important too, because you see practically how they work and why the libraries are better because of their optimizations.

That's my two cents. I am not an expert and, from what I read here, there are very capable people around, maybe there have another advice.
What's the channel name?
 
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fastlanedoll

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Didnt read the entire thread.

I'm interested in it, but don't know where I can reliably learn about it in order to adapt it into business.
 

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Hi all, just wanted to chip in as someone who works in this space. (Data Scientist)

For those considering getting into the field, I'd recommend considering this article (especially point #8). Don't take it too literally - but this echos a lot of the commentary I've personally made about the direction of the field.

This is pretty much spot on, based on my experience. After a few years bouncing around data science roles plus freelancing, it looks to me like many companies don't really have use for AI/ML as-promised. And often they're lacking the infrastructure to support model deployment even if they have a use case. Of course they don't know that yet, so it's a great job market now. This might mean a near-term bubble.

But as companies advance their tech (largely: get on cloud!), there may well be a point where machine learning becomes relevant for these companies. But I expect the data science landscape to have changed largely by then. The statistics side of this is already all but irrelevant for the practitioner. That matters for the people at Google/Amazon/Microsoft developing the algorithms; but for everyone else, you can call them as an API from your favorite cloud provider. This means (IMO) that the "data science" many have learned (fitting models with sklearn) will be irrelevant, and a developer skillset more and more important.

Anyways, exciting times. I'm working on a "prediction-as-a-service" type of product now that will hopefully lower the barrier to entry to machine learning for smaller companies who are used to working in Excel.

Excited to hear more about what you guys are doing in this space and potentially partnering up!
 

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