
Dissecting Relu: A desceptively simple activation function
What is this post about? This is what you will be able to generate and understand by the end of this post. This is the
What is this post about? This is what you will be able to generate and
We never Had Truly Understood the Bias-Variance Trade-off!!! In this interview with Prof. Mikhail Belkin,
What is This post about? The interview with the lead author of the paper: Prof.
“There are a lot more papers written than there are widely read!” (Tom Mitchell) Prof.
What will you learn? The video below, delivers the main points of this blog post
What will you learn? This post is also available to you in this video, should

What is this post about? This is what you will be able to generate and understand by the end of this post. This is the

We never Had Truly Understood the Bias-Variance Trade-off!!! In this interview with Prof. Mikhail Belkin, we will discuss his amazing paper: “Reconciling modern machine learning

What is This post about? The interview with the lead author of the paper: Prof. Mikhail Belkin Together we will analyze an amazing paper entitled:

“There are a lot more papers written than there are widely read!” (Tom Mitchell) Prof. Tom Mitchell is one of the giants of machine learning

What will you learn? The video below, delivers the main points of this blog post on Stochastic Gradient Descent (SGD): (GitHub code available in here)

What will you learn? This post is also available to you in this video, should you be interested 😉 https://www.youtube.com/watch?v=znqbtL0fRA0&feature=youtu.be In our previous post, we
🔴Join me LIVE for the next reading session of the book 𝗔𝗰𝘁𝗶𝘃𝗲 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲. This session will work out a numeric example for 𝗕𝗮𝘆𝗲𝘀' 𝗥𝘂𝗹𝗲.
📷𝗪𝗛𝗘𝗥𝗘:
📷𝗪𝗵𝗮𝘁 𝗧𝗶𝗺𝗲: 21:00 (Australian Eastern Standard Time) 🔥
🚨 Going LIVE this Thursday (22:00 AEST)
Kicking off a live reading of
📘 Active Inference: The Free Energy Principle in Mind, Brain, and Behavior
We start with:
🧠 Perception as Unconscious Inference👇
#Neuroscience #MachineLearning #AI
The Beauty that is the Delta Rule In general, there are 2 main ways to
The Perceptron Training Rule It is important to learn the training process of huge neural
ECML-PKDD-2019 on EBFDD networks for Anomaly Detection This paper introduces the Elliptical Basis Function Data
What will you Learn in this Post? Neural Networks are function approximators. For example, in
🔴Join me LIVE for the next reading session of the book 𝗔𝗰𝘁𝗶𝘃𝗲 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲. This session will work out a numeric example for 𝗕𝗮𝘆𝗲𝘀' 𝗥𝘂𝗹𝗲.
📷𝗪𝗛𝗘𝗥𝗘:
📷𝗪𝗵𝗮𝘁 𝗧𝗶𝗺𝗲: 21:00 (Australian Eastern Standard Time) 🔥
🚨 Going LIVE this Thursday (22:00 AEST)
Kicking off a live reading of
📘 Active Inference: The Free Energy Principle in Mind, Brain, and Behavior
We start with:
🧠 Perception as Unconscious Inference👇
#Neuroscience #MachineLearning #AI
