The omnipresence of technology nowadays has made it commonplace to read news about AI, just a quick glance at today’s headlines, and I get:

• This Powerful AI Technique Led to Clashes at Google and Fierce Debate in Tech.
• How A.I.-powered companies dodged the worst damage from COVID
• AI technology detects ‘ticking time bomb’ arteries
• AI in Drug Discovery Starts to Live Up to the Hype
• Pentagon seeks commercial solutions to get its data ready for AI

Topics from business, manufacturing, supply chain, medicine and biotech and even defense are covered in those news... read more

Background

After many years of a corporate career (17) diverging from computer science, I have now decided to learn Machine Learning and in the process return to coding (something I have always loved!).

To fully grasp the essence of ML I decided to start by coding a ML library myself, so I can fully understand the inner workings, linear algebra and calculus involved in Stochastic Gradient Descent. And on top learn Python (I used to code in C++ 20 years ago).

I built a general purpose basic ML library that... read more

Background

After many years of a corporate career (17) diverging from computer science, I have now decided to learn Machine Learning and in the process return to coding (something I have always loved!).

To fully grasp the essence of ML I decided to start by coding a ML library myself, so I can fully understand the inner workings, linear algebra and calculus involved in Stochastic Gradient Descent. And on top learn Python (I used to code in C++ 20 years ago).

I built a general purpose basic ML library that... read more

For the seemingly small project I undertook of creating a machine learning neural network that could learn by itself to play tic-tac-toe, I bumped into the necesity of implementing at least one momentum algorithm for the optimization of the network during backpropagation.

And since my original post for the TicTacToe project is quite large already, I decided to post separately these optimization methods and how did I implement them in my code.

Adam

source

Adaptive Moment Estimation (Adam) is an optimization method that computes adaptive learning rates for each weight and bias. In addition to storing an... read more

It must sound crazy that in this day and age, when we have such a myriad of amazing machine learning libraries and toolkits all open sourced, all quite well documented and easy to use, I decided to create my own ML library from scratch.

Let me try to explain; I am in the process of immersing myself into the world of Machine Learning, and to do so, I want to deeply understand the basic concepts and its foundations, and I think that there is no better way to do so than by creating myself all the... read more

For the seemingly small project I undertook of creating a machine learning neural network that could learn by itself to play tic-tac-toe, I bumped into the necesity of implementing at least one momentum algorithm for the optimization of the network during backpropagation.

And since my original post for the TicTacToe project is quite large already, I decided to post separately these optimization methods and how did I implement them in my code.

Adam

source

Adaptive Moment Estimation (Adam) is an optimization method that computes adaptive learning rates for each weight and bias. In addition to storing an... read more

In the midst of a global pandemic caused by the SARS-COV2 coronavirus; I decided to start blogging. I wanted to blog since a long time, I have always enjoyed writing, but many unknowns and having “no time” for it prevented me from taking it up. Things like: “I don’t really know who my target audience is”, “what would my topic or topics be?”, “I don’t think I am a world-class expert in anything”, and many more kept stopping me from setting up my own blog. Now seemed like a good time as any so with those and tons of other... read more

In the midst of a global pandemic caused by the SARS-COV2 coronavirus; I decided to start blogging. I wanted to blog since a long time, I have always enjoyed writing, but many unknowns and having “no time” for it prevented me from taking it up. Things like: “I don’t really know who my target audience is”, “what would my topic or topics be?”, “I don’t think I am a world-class expert in anything”, and many more kept stopping me from setting up my own blog. Now seemed like a good time as any so with those and tons of other... read more

The omnipresence of technology nowadays has made it commonplace to read news about AI, just a quick glance at today’s headlines, and I get:

• This Powerful AI Technique Led to Clashes at Google and Fierce Debate in Tech.
• How A.I.-powered companies dodged the worst damage from COVID
• AI technology detects ‘ticking time bomb’ arteries
• AI in Drug Discovery Starts to Live Up to the Hype
• Pentagon seeks commercial solutions to get its data ready for AI

Topics from business, manufacturing, supply chain, medicine and biotech and even defense are covered in those news... read more

Background

After many years of a corporate career (17) diverging from computer science, I have now decided to learn Machine Learning and in the process return to coding (something I have always loved!).

To fully grasp the essence of ML I decided to start by coding a ML library myself, so I can fully understand the inner workings, linear algebra and calculus involved in Stochastic Gradient Descent. And on top learn Python (I used to code in C++ 20 years ago).

I built a general purpose basic ML library that... read more

For the seemingly small project I undertook of creating a machine learning neural network that could learn by itself to play tic-tac-toe, I bumped into the necesity of implementing at least one momentum algorithm for the optimization of the network during backpropagation.

And since my original post for the TicTacToe project is quite large already, I decided to post separately these optimization methods and how did I implement them in my code.

Adam

source

Adaptive Moment Estimation (Adam) is an optimization method that computes adaptive learning rates for each weight and bias. In addition to storing an... read more

The omnipresence of technology nowadays has made it commonplace to read news about AI, just a quick glance at today’s headlines, and I get:

• This Powerful AI Technique Led to Clashes at Google and Fierce Debate in Tech.
• How A.I.-powered companies dodged the worst damage from COVID
• AI technology detects ‘ticking time bomb’ arteries
• AI in Drug Discovery Starts to Live Up to the Hype
• Pentagon seeks commercial solutions to get its data ready for AI

Topics from business, manufacturing, supply chain, medicine and biotech and even defense are covered in those news... read more

It must sound crazy that in this day and age, when we have such a myriad of amazing machine learning libraries and toolkits all open sourced, all quite well documented and easy to use, I decided to create my own ML library from scratch.

Let me try to explain; I am in the process of immersing myself into the world of Machine Learning, and to do so, I want to deeply understand the basic concepts and its foundations, and I think that there is no better way to do so than by creating myself all the... read more

As an entry point to learning python and getting into Machine Learning, I decided to code from scratch the Hello World! of the field, a single neuron perceptron.

What is a perceptron?

A perceptron is the basic building block of a neural network, it can be compared to a neuron, And its conception is what detonated the vast field of Artificial Intelligence nowadays.

Back in the late 1950’s, a young Frank Rosenblatt devised a very simple algorithm as a foundation to construct a machine that could learn to perform different tasks.

In its essence, a perceptron is nothing... read more

For the seemingly small project I undertook of creating a machine learning neural network that could learn by itself to play tic-tac-toe, I bumped into the necesity of implementing at least one momentum algorithm for the optimization of the network during backpropagation.

And since my original post for the TicTacToe project is quite large already, I decided to post separately these optimization methods and how did I implement them in my code.

Adam

source

Adaptive Moment Estimation (Adam) is an optimization method that computes adaptive learning rates for each weight and bias. In addition to storing an... read more

Background

After many years of a corporate career (17) diverging from computer science, I have now decided to learn Machine Learning and in the process return to coding (something I have always loved!).

To fully grasp the essence of ML I decided to start by coding a ML library myself, so I can fully understand the inner workings, linear algebra and calculus involved in Stochastic Gradient Descent. And on top learn Python (I used to code in C++ 20 years ago).

I built a general purpose basic ML library that... read more

It must sound crazy that in this day and age, when we have such a myriad of amazing machine learning libraries and toolkits all open sourced, all quite well documented and easy to use, I decided to create my own ML library from scratch.

Let me try to explain; I am in the process of immersing myself into the world of Machine Learning, and to do so, I want to deeply understand the basic concepts and its foundations, and I think that there is no better way to do so than by creating myself all the... read more

I am lately trying to take on coding again. It had always been a part of my life since my early years when I learned to program a Tandy Color Computer at the age of 8, the good old days.

Tandy Color Computer TRS80 III

Having already programed in Java, C# and of course BASIC, I thought it would be a great idea to learn Python since I have great interest in data science and machine learning, and those two topics seem to have an avid community within Python coders.

For one of my starter quick programming... read more

Background

After many years of a corporate career (17) diverging from computer science, I have now decided to learn Machine Learning and in the process return to coding (something I have always loved!).

To fully grasp the essence of ML I decided to start by coding a ML library myself, so I can fully understand the inner workings, linear algebra and calculus involved in Stochastic Gradient Descent. And on top learn Python (I used to code in C++ 20 years ago).

I built a general purpose basic ML library that... read more

In the midst of a global pandemic caused by the SARS-COV2 coronavirus; I decided to start blogging. I wanted to blog since a long time, I have always enjoyed writing, but many unknowns and having “no time” for it prevented me from taking it up. Things like: “I don’t really know who my target audience is”, “what would my topic or topics be?”, “I don’t think I am a world-class expert in anything”, and many more kept stopping me from setting up my own blog. Now seemed like a good time as any so with those and tons of other... read more