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Following.

Thanks sirRiddy for this!

To start with, two emerging buzzwords these days are Machine Learning and Artificial Intelligence. What's the clear-cut difference between these two? Practical applications in each area would be great!

Also, what are some great ML startups ideas one could start working on?

Thanks!

**taking notes**

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Ok.

This is home.

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sirRiddy:
Machine Learning(ML), a way to do AI, is gaining traction now because of things like when you make a typo,
for instance, while searching in Google,
it gives you the message: "Did you mean..."? This is the result of one of Google's machine learning algorithms;
a system that detects what searches you make a couple seconds after making a certain search.
For example, suppose you were searching for Who is Okocha' on Google but accidentally typed 'Who is pkpcha'. After the search,
you'd probably realise you typed it wrong and you'd go back and search for 'Okocha' a couple of seconds later.
Google’s algorithm recognises that you searched for something a couple of seconds after searching something
else, and it keeps this in mind for future users who make a similar typing mistake. As a result, Google
'learns' to correct it for you. [3]
So, ML is an attempt to make machines learn from data themselves. A major domain where it is being explored is the
understanding of the human genome.
This is how it works, in a very simplistic way.
1. You have a dataset, usually large.
2. Your system 'learns' from those dataset
3. You have ML algorithms explore patterns in those datasets
4. This knowledge can be applied to an array of tasks like speech recognition, image recognition etc

Alexa and the rest were programmed and would fail in other domains. With ML algorithms, systems can be
applied to different array of tasks, made to learn from data and apply this knowledge to new domains
while trying to solve tasks intelligently.

References
1. https://en.wikipedia.org/wiki/Artificial_intelligence
2. https://en.wikipedia.org/wiki/DeepMind
3. http://www.wired.co.uk/article/machine-learning-ai-explained

I get your explanation bro but I think you only have the "bookish" understanding [ I'm sorry for saying this].

The steps you outlined are important but you need to understand many processes that goes on for them to be accomplished. First, ask yourself "how did Google get these datasets?"
Second, "which systems learn from these datasets?", what is a system? Are they series of codes, programs, or written algorithms?
Third, what are the ML algorithms that can explore this pattern? How do they explore this pattern?

Lastly, you are right about step 4 outlined above

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sirRiddy:
Thank you for your input. No need to apologize at all for expressing your thoughts and critique
I was actually talking generally and not in terms of how Google works or how a specific
Machine Learning technique works, that is why I called it simplistic.
By the way, I do not think there is anything wrong with the 'bookish' definition or understanding of a concept.
Both research and academia work together to explore the frontier of knowledge.
I am glad you offered your take on this. Feel free to offer more insights and/or criticisms.

Good response, maybe he never knew one can modify google search engine.
Are you working on this?

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sirRiddy:
Thank you . Your question is not clear, working on what?

I mean researching on it

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sirRiddy:
Yes, I have very little knowledge in the area, so I thought those
who have worked there or have interest in it can help facilitate the
learning process. I am basically interested in the current state of the field and
current research concerns, so I want to avoid reinventing the wheel as much as possible.

OK! It sounds interesting though am not into computer language.

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sirRiddy:
Thank you for your input. No need to apologize at all for expressing your thoughts and critique
I was actually talking generally and not in terms of how Google works or how a specific
Machine Learning technique works, that is why I called it simplistic.
By the way, I do not think there is anything wrong with the 'bookish' definition or understanding of a concept.
Both research and academia work together to explore the frontier of knowledge.
I am glad you offered your take on this. Feel free to offer more insights and/or criticisms.

I'm sorry if I sounded rude or offensive. I hope my apology is accepted?

Now to the topic, knowing ML algorithms is not the problem but knowing when to apply them is.

I've worked with people who use Dimension Reduction techniques instead of Regularization, Regression instead of Decision trees and the list is endless.

There are online communities such as R bloggers, Stack overflow, and so on one can learn the latest trend from and don't forget to be involved on online competitions such as Kaggle and other hackathons.

There is a thread similar to this here on nairaland but I hope this could be different by us sharing our codes and assisting one another instead of engaging in too much talk.

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Wow... I will stay off your thread I guess.

neahyo:
Wow... I will stay off your thread I guess.

I agree with you on the bookish knowledge of his. He seem not to have had some "hands on" experience on what he is talking about. Best to stay off his thread #yuck!

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sirRiddy:
You seem to have a big issue with comprehension and that is your problem.

No, I think you seem to have big issue with understanding how the machine language practically works and that's your problem

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sirRiddy:
That is quite true. I have a very limited knowledge on practical AI generally. If you read the first part, I already clearly stated this as well as the
purpose of my creating the thread.
But you are just devoid of any reasonable comprehension skill which is way more important than
any sort of transient knowledge. Will you be able to deal with that? None of my business.

I could have shed more light and add some enlightenment on your ignorance in the practical aspect of machine language , but with your manner of approach on responses, I'll rather let you be. Apologies for ever commenting on your thread

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sirRiddy:
Screw you and your stupid light. Go f.uck yourself

You are disgustingly rude

From your post OP I thought you were matured but reviewing your comment and word useage left much to be desired. Grow up and comment like a professional not like a kid.

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