If you are probably new to blockchain, brace yourself, after this story, you will have complete idea of blockchain and how it works.
Before You get started, I recommend you to check out the previous story here “The philosophy of blockchain” that helps understanding the big picture.
The Block chain technology is relatively simpler than other technologies in CS as it has a lot of understandable concepts and consensus, so you got nothing to be scared when it comes to learning Blockchain so Relax….
Let me start with a simple question = what’s blockchain??
Blockchain = A chain of blocks…
Understanding with “What is” is how we often learn things, but the moment a “why” question of “what” has been asked/raised, we won’t even understand the question, LET ALONE THE ANSWER.
if you don’t understand the philosophy of a technology , you won’t probably understand the practical and social implications of that technology in great depth.
Understanding the why of what of which is very important.
Alright, let’s get started.
to understand the philosophy of blockchain, let’s understand what’s happening right now.
The internet surely changed the game in technology , solving a bunch of problems in search, communication, delivery…
I am typing this on 2, April, 2021, 10:10 AM (UTC) to let the people know the vision & overview of this publication (Blockchain, crypto, Defi, Web3.0) and intention of mine for this publication.
My name has been Madhu Sanjeevi (Mady) being a software enthusiast & engineer for more than 5 years till this point, worked for few+ companies over the years as an s/w engineer building mobile applications, web applications and AI applications,
I have good amount of knowledge in building software products and Have interest in sharing my knowledge to other people through blogs and meetups.
Recently I started an AI startup called bitsoup.ai and I have had couple of fun products to build through the startup,
so far I have been kinda a guy who does training/fine tuning/improving deep learning models and be done with it but the first time after starting a startup , I had the need to deploy the models I built to the whole world.
Initially I thought , well, its okay I prefer AWS with 12 month free tier (yeah I quit my job and am in debt ) but immediately realised after building small services in flask and django…
Hello All, This is my first story in this publication, I wanna make it as useful as possible.
So in this story I am gonna take the most famous dataset in ML community called MNIST, explore it as much as possible and finally build good models with conclusions.
Note: This story reading time is way more than Medium says it is and you think it is so if you are serious about learning you gotta give that time.
→ It has the size of 28*28 black & white images of hand written digits
→ It’s probably one of the first…
you feel it or not, you think it or not, you believe it or not, you admit it or not,
This happens to every single human being in this planet. You tend to get affected by your surrounding people at all points of time irrespective of your beliefs, your passions, your goals, your successes and etc...
and this does not happen consciously, it happens to you all the time subconsciously.
Yeah that’s right “Subconsciously”.
it happens so subconsciously that you don’t even know that it’s happening.
I wanna share an idea of “Why”, “How” that is happening in this story
Welcome back to the chapter 14 GAN’s series, this is the 3rd story connected to the previous 2 stories.
I hope you have gone through the last stories or you have already an idea about GAN’s and it’s types a bit.
In this story, I mainly wanna talk about different new ideas like Pix2Pix, CycleGAN’s with it’s Math and Training.
I wanna share the author’s views from ground so you can train these for your problems or do a little more work around as part of your research.
Just a little
Recap from last stories
→ Gans learn the distribution…
what’s up folks?? how are you doin’??
In the last story I talked about GAN’s with Math so this story I am gonna talk about different types of GAN’s that are invented since vanilla GAN’s.
Let’s roll baby!
Gan’s were introduced by Ian Goodfellow et al. in 2014, since then a lot of researchers from big companies have come up with a lot of different cool ideas to improve the gan’s training and gan’s performance.
Before I talk about it, Let me just give you a quick
Recap from the last story.
Gan’s have two networks
Hmmm how do I start writing this story ???
Love you leCun.
I have been writing stories about a lot of different algorithms so far and all are discriminative algorithms, but this story is all about Generative models so let me quickly detail you about what the differences are
One of the most exciting developments in AI is #DeepRL. Today we are gonna talk about that #getready
In this story I only talk about two different algorithms in deep reinforcement learning which are Deep Q learning and Policy Gradients.
Before I get started , I assume you have checked my other stories from the previous chapter “Reinforcement learning Part 1 and part 2. if not please check those out otherwise it’s difficult to catch up with me.