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

ChrisV

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Artificial Intelligence and Machine Learning are likely going to be the biggest boons of the 21st century.

Possibly one of the biggest technological boon the world has ever seen.

The Entrepreneurship opportunities are going to be endless.

I wanted to make a space for those pursuing AI or interested in AI to share resources and any type of AI related

So are you pursuing AI? What's your story? What interests you about AI? Have any resources to share?

Or feel free to just talk about anything AI or ML related.

@ZF Lee , @Strategery , @David Moyses

Feel free to tag anyone who you know that's involved in Data Science, Machine Learning or AI

So what interests you about the world of AI?
 

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ZF Lee

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Artificial Intelligence and Machine Learning are likely going to be the biggest boons of the 21st century.

Possibly one of the biggest technological boon the world has ever seen.

The Entrepreneurship opportunities are going to be endless.

I wanted to make a space for those pursuing AI or interested in AI to share resources and any type of AI related

So are you pursuing AI? What's your story? What interests you about AI? Have any resources to share?

Or feel free to just talk about anything AI or ML related.

@ZF Lee , @Strategery , @David Moyses

Feel free to tag anyone who you know that's involved in Data Science, Machine Learning or AI

So what interests you about the world of AI?
Haha I’m just taking some data analytics courses in university, and I would have never got into the field in the first place, if I didn’t have a great lecturer for my first year.

In high school, for elementary statistics, they just threw all the Greeks at you and you have to memorize everything without truly comprehending their roles.

But my lecturer was different.

He took real-life problems that spiraled out of control (eg newspaper reports that miscommunicated data and led to government F*ck-ups and societal backlash) and showed us how the concepts come into play.

So I’m in the field more for the problem-solving, and the background story, that gives data its meaning, rather than the numbers or lingo themselves.

Exploration is the key word.

For my current freelance copywriting jobs, I’m beginning to wonder if there were more effective methods of research, rather than just qualitative surveying and forum scrolling.

Or, if you will, I’m leaning towards a left-brained logical way of research, as sometimes leaving research to ‘wing it’ can result in some very deceptive interpretations.
 

Empires

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I am not currently in the AI space but have plans for it in the future. The sheer amount of opportunity in the space is incredible. Will surely change an insane amount of industries over time.
 
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ChrisV

ChrisV

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He took real-life problems that spiraled out of control (eg newspaper reports that miscommunicated data and led to government F*ck-ups and societal backlash) and showed us how the concepts come into play.

So I’m in the field more for the problem-solving, and the background story, that gives data its meaning, rather than the numbers or lingo themselves.
Yes! Statistics is boring in and of itself. It's what you can do with Statistics that's exciting.

The analogy I like to use is... Math is boring, right? Physics is boring, right?

But what if you could use your knowledge of Math and Physics to create the fastest Ferrari the world has ever seen. Now it's not so boring now is it? So the fields are always boring in a vacuum, but they become exciting when you see what they can help you accomplish.

Another great example comes from my favorite movie: Moneyball.

Stats is boring right? But in the early 2000s Harvard Statistician Paul DePodesta teamed up with Billy Beane and the Oakland A's to use statistics to create one of the most impressive baseball rosters of all time. They almost beat the Yankees in the World Series, but did it for one eighth of the price. Just by using Stats.

I made a quick 3 video Moneyball Playlist that I think illustrates everything nicely, even for people who have seen the movies


Human decision making is flawed because of a number of biases. Stats eliminates those.

In the Moneyball situation, certain players were overlooked becasue they were funny looking, had an ugly girlfriend, had a weird pitching stance. So most teams didn't realize how amazing they were as players because human decision making is biased.


 
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Strategery

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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.
 
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ChrisV

ChrisV

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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.
Hm, not all versions need to be accessed from the terminal. If you're more comfortable you can launch it from Anaconda, or your web browser.

Honestly though, the Terminal is sooooooo useful when coding, and you might find yourself preferring it. But whatever you prefer for now. But I don't believe that the terminal is a requirement for running Jupyter.
 

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So what interests you about the world of AI?
I love the endless applications it has. Literately, any thing can benefit from Machine Learning.

I was into ML for a while (before I got distracted with games programming) and loved it. But it felt like climbing the Everest. There's so much to learn that's one of the fields that really require specific education to get somewhere.

I played around with ML for finance and betting, it was fun. I have some real projects in mind, but they aren't my current priority. I specially like ML for real estate (although getting good data seems tricky).
 

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I'm interested in seeing what developments AI makes, and maybe getting into a vertical aligned with it. Currently run 2 domains meant to generate b2b AI SaaS leads, will see how that goes :p. Big problem I've found is predicting buyer intent with b2b products, especially AI. Perhaps product reviews or specific white paper detailing a specific problem are the way to go.
 

srodrigo

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I'm actually thinking about some fields that could be packed with opportunities for ML and are in my areas of interest:
  • Marketing & Sales: this is only going to be more necessary over time. Reaching more customers, increasing discoverability, or making the most out of each customer, are things that will always need to be improved.
  • Health: staying alive is always going to be a high priority need.
  • Real Estate: I have my doubts here. Having a roof is definitely a high priority need, so it should be a good market. However, in some developed countries with very old population, I think the market can eventually blow up when there are too many abandoned houses (see Japan giving houses away). I might be completely wrong, but some countries could see a population decrease and have more houses than needed.
 

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ZF Lee

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Perhaps product reviews or specific white paper detailing a specific problem are the way to go.
I write white papers myself, and I often read up other competing white papers.

Some writers just cannibalize each other for the same shitty stats, or just throw in data from irrelevant articles or websites that purport themselves to be 'summaries of complicated government and scientific papers'.

Just to illustrate the situation...

A client asked me to change a certain market growth statistic, since it was similar to that from a competing research firm's white paper. I went to look for a different estimate from another source, and along the way, I found lots of other articles and papers on the similar topic with the SAME STATISTIC BY THE COMPETITOR FIRM, even in one paper from the Australian international trade council website. :inpain:

So...if you want a truly great white paper, you still need the firm to do its own research and surveys.
Expensive, but you'll cover the gaps.
 
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ChrisV

ChrisV

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My story: I run a Data Science company. I work with a number of researchers and various corporations to help them solve problems accurately through data. I'm hoping to expand my skills to encompass more Machine Learning techniques into my research. I got into Data Science becasue I just love Science. Not so much chemistry, or physics or anything else when you think of "science," but just the scientific method. The philosophy of science. The idea that rather that rely on intuition or faith, we actually test our ideas to make sure they're true.

Science vs Faith.png

I've found that with good data you can accurately answer pretty much any question you can think of.

Data Science gave me the opportunity to basically run quasi-experiments finding the answer to almost any question I needed to. Traditionally with science, it was a lot of work testing a hypothesis. You'd have to set up experiments, conduct long questionnaires, etc. Not so with Data Science.

From a Medium post I wrote a while back:

The world is changing. All sorts of new technology is on the horizon. Ever wonder how Amazon knows exactly what books you might like? How Pinterest figures out which ‘pins’ might interest you. How Apply Music or Spotify finds new songs that you absolutely fall in love with. How do these machines all this out? How are our devices becoming so intelligent? The answer is Data Science.

We now have the ability to track every click, swipe, ‘like,’ and repost that we want.

Within this data is enormous insights about consumer behavior and even general psychology. Companies have enormous amounts of Data and can do all sorts of incredible things with it. Data Scientist: The Sexiest Job of the 21st Century. Data Science can call presidential races, can tell you which movie is best for you based on your tastes and moods. Netflix upgraded itself from a simple DVD Mailing service and made itself a household name by applying algorithms that figure out which movies you’re most likely to enjoy.

Data Science can show you new music that you would like based on your tastes and even mood. Mercedes-Benz for instance is experimenting with heart-rate sensors to determine your mood so it can decide what music to play for you. It can tell if you’re in a relaxed mood and just want some relaxing music, or if you’re in an upbeat mood and want something more energetic.


And here's the full Medium post for anyone interested.

 

srodrigo

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My story: I run a Data Science company. I work with a number of researchers and various corporations to help them solve problems accurately through data. I'm hoping to expand my skills to encompass more Machine Learning techniques into my research. I got into Data Science becasue I just love Science. Not so much chemistry, or physics or anything else when you think of "science," but just the scientific method. The philosophy of science. The idea that rather that rely on intuition or faith, we actually test our ideas to make sure they're true.

View attachment 26717

I've found that with good data you can accurately answer pretty much any question you can think of.

Data Science gave me the opportunity to basically run quasi-experiments finding the answer to almost any question I needed to. Traditionally with science, it was a lot of work testing a hypothesis. You'd have to set up experiments, conduct long questionnaires, etc. Not so with Data Science.

From a Medium post I wrote a while back:

The world is changing. All sorts of new technology is on the horizon. Ever wonder how Amazon knows exactly what books you might like? How Pinterest figures out which ‘pins’ might interest you. How Apply Music or Spotify finds new songs that you absolutely fall in love with. How do these machines all this out? How are our devices becoming so intelligent? The answer is Data Science.

We now have the ability to track every click, swipe, ‘like,’ and repost that we want.

Within this data is enormous insights about consumer behavior and even general psychology. Companies have enormous amounts of Data and can do all sorts of incredible things with it. Data Scientist: The Sexiest Job of the 21st Century. Data Science can call presidential races, can tell you which movie is best for you based on your tastes and moods. Netflix upgraded itself from a simple DVD Mailing service and made itself a household name by applying algorithms that figure out which movies you’re most likely to enjoy.

Data Science can show you new music that you would like based on your tastes and even mood. Mercedes-Benz for instance is experimenting with heart-rate sensors to determine your mood so it can decide what music to play for you. It can tell if you’re in a relaxed mood and just want some relaxing music, or if you’re in an upbeat mood and want something more energetic.


And here's the full Medium post for anyone interested.

How long did it take you to learn enough to start your company?
 
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ChrisV

ChrisV

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How long did it take you to learn enough to start your company?
That's a good question. It's actually pretty fast if you get the right system. Much of the time that it took was due to mistakes, ie learning a bunch of unimportant crap.

I code in R. I spent a lot of time learning the fundamentals of base R, only to realize that nobody really uses base R. So I had to go back and learn the Tidyverse. I learned a lot of python just to realize that python didn't suit my needs.

I think the best way to learn Data Science is to just do Data Science. Find some practice problems and competitions that are similar to what you want to accomplish and use StackOverflow and Google to fill in the details.

If you find the right course, you can learn it fast. But so many of these places waste time teaching "the fundamentals." F--- the fundamentals. You'll waste so much time learning crap you'll never use.

The only site I found who had really good courses was this:


I do think it's important to understand the fundamentals of scientific philosophy though.

I mean i guess it depends on what you want to do though.

I wrote a post on learning R fast, but you may be able to gleam lessons from other programming languages.

The big thing is to grasp the Pareto principle... 80% of the important stuff will come from 20% of the knowledge available. The trick is to just figure out what that 20% is in your field.

 
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ChrisV

ChrisV

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Attorney General Anne Milgram uses "Moneyball"-esque techniques to reform the criminal justice system, with great success.

Anne Milgram: Why smart statistics are the key to fighting crime


When she became the attorney general of New Jersey in 2007, Anne Milgram quickly discovered a few startling facts: not only did her team not really know who they were putting in jail, but they had no way of understanding if their decisions were actually making the public safer. And so began her ongoing, inspirational quest to bring data analytics and statistical analysis to the US criminal justice system.
 

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