Getting started with AI

Published in

BuzzRobot

6 min readJan 8, 2018

One of the breakthrough of Technology in 21st Century is Artificial Intelligence.It started to adapt various fields in the industry and became an emerging technology.So that there is a huge demand for AI Developers and Researcher and many of the organization and individuals contributed their work in AI which leads to the topic called Machine learning and Deep Learning.Many of the Developer are choosing AI as their career but they don’t know How to Start Learning AI ?. So in this blog, I am going to share some information and resources to learn AI.

The first Step Learn Difference Between AI, Machine Learning, and Deep Learning:

Artificial Intelligence:

Any techniques that enable the computer to mimic human intelligence using logic,if-then rules, Decision trees and machine learning including Deep learning is called Artificial Intelligence.

Eg: Google Assistant

Machine Learning:

A subset of AI that includes abstruse statistical techniques that enable machines to improve tasks with experience.The category includes Deep Learning.

Eg: Predicting the house rate by the past available data

Deep Learning:

The subset of Machine Learning composed of Algorithms that permit software to train itself to perform tasks like speech and image recognition by exposing multi-layered neural networks to vast amounts of data.

Eg: Object Detection whether its a cat or dog using pre-trained models.

Programming Knowledge For AI :

Python (Since it has many community support and framework to develop efficient AI programs).To get started with python refer the below link

https://www.programiz.com/python-programming

Python Books:

https://mega.nz/#F!jghEBTKJ!KK7R3EoVBSngO5lK5RWEFw

Python Documentation:

https://docs.python.org/3/

Little Bit of SQL:

https://www.w3schools.com/sql/default.asp

That’s it, I think this much is enough to get started.

REMEMBER:

While watching videos kindly make the note of important keywords, if you didn’t understand watch it again or browse it or comment on my blog I will help you.Please don’t SKIP.

Concepts Of AI:

When you are going to start studying about AI you should be well clear about their terminology and their algorithms.Because different use cases working with different AI algorithm.Eg : For prototyping, any game powered by AI most of them will be using MIN-MAX ALGORITHM. So you should be clear with AI concept when you are going to do a project in that.I can give you some major algorithm and concepts and their link below:

Intelligent Agents and Uninformed Search
Heuristic Search
Adversarial Search and Games
Machine Learning
Constraint Satisfaction problems
Reinforcement Learning
Logical Agents
Natural Language Processing
Deep Learning

It will be theory part so make your mindset according to that and start learning it.The useful links are:

I recommend these two are the best beginner course for AI and its FREE.

PICK UP THE CORRECT CATEGORY IN AI:

After reading the previous sub-topic you should be clear with the concepts of it.Now it’s the time to pick the right category from it.Since to make my blog short and brief I will discuss only the emerging category of AI by their popularity.

1.Machine Learning:

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI.

Useful Course Links and Blogs for Machine Learning:

I think this much is enough to get started with ML and mostly you will be covering all the major topics of it.

BOOKS FOR REFERENCE:

BLOG LINKS FOR ML:

2.Natural Language Processing:

Natural language processing (NLP) is a field of computer science, artificial intelligence concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language data.Challenges in natural language processing frequently involve speech recognition, natural language understanding, and natural language generation.

Links For NLP:

3.Deep Learning:

Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.

Links for Deep Learning:

4.Robotics:

Artificial intelligence (AI) is arguably the most exciting field in robotics. It’s certainly the most controversial: Everybody agrees that a robot can work in an assembly line, but there’s no consensus on whether a robot can ever be intelligent.

Like the term “robot” itself, artificial intelligence is hard to define. Ultimate AI would be a recreation of the human thought process — a man-made machine with our intellectual abilities. This would include the ability to learn just about anything, the ability to reason, the ability to use language and the ability to formulate original ideas. Roboticists are nowhere near achieving this level of artificial intelligence, but they have made a lot of progress with more limited AI. Today’s AI machines can replicate some specific elements of intellectual ability.

https://youtu.be/QVdQM47Av20

Crazy to learn about these Just Follow these links:

Thats it but there are many works of AI you can google it and check if you like .

YOUTUBE CHANNELS TO FOLLOW:

1)Siraj Raval — https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A

2)Sentdex — https://www.youtube.com/user/sentdex

3)DeepLearning.TV — https://www.youtube.com/channel/UC9OeZkIwhzfv-_Cb7fCikLQ

4)Google AI Adventures — https://www.youtube.com/playlist?list=PLIivdWyY5sqJxnwJhe3etaK7utrBiPBQ2

5)Stanford University School of Engineering — https://www.youtube.com/user/stanfordeng/playlists

GOOGLE BLOGS:

https://cloud.google.com/blog/big-data/2017/01/learn-tensorflow-and-deep-learning-without-a-phd

MOST USED FRAMEWORK FOR THE DEVELOPMENT OF AI:

I AM AN AI DEVELOPER:

After completely experienced with these resources and you are able to develop an AI application then woow congrats you are an AI Developer.These are just a beginner resources for your AI Career.Hope you like content in my blog.

Sharing is worth than anything.Kindly share this blog to your friends.

Feel free to comment your doubts or feedback about this blog in comment section below..