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The Backpropagation Algorithm-PART(1): MLP and Sigmoid
What is this post about? The training process of deep Artificial Neural Networks (ANNs) is based on the backpropagation algorithm.
Dissecting Relu: A desceptively simple activation function
What is this post about? The Rectified Linear Unit (Relu) will be beautifully dissected in this popst: https://www.youtube.com/watch?v=Un9A90mfO54 This is
An interview with Prof. Mikhail Belkin
We never Had Truly Understood the Bias-Variance Trade-off!!! In this interview with Prof. Mikhail Belkin, we will discuss his amazing
Reconciling modern machine learning practice and the bias-variance trade-off
What is This post about? The interview with the lead author of the paper: Prof. Mikhail Belkin Together we will
An interview with Prof. Tom Mitchell
“There are a lot more papers written than there are widely read!” (Tom Mitchell) Prof. Tom Mitchell is one of
Stochastic Approximation to Gradient Descent
What will you learn? The video below, delivers the main points of this blog post on Stochastic Gradient Descent (SGD):
Back-propagation with Cross-Entropy and Softmax
What will you learn? This post is also available to you in this video, should you be interested 😉 In
COVID-19 Analysis
Studying and Predicting the Progress of COVID-19 using Pandas and ARIMA COVID-19 has been around for nearly 4 months since
Deriving the Gradient Descent Rule (PART-2)
What Will You Learn? In our previous post, we have talked about the meaning of gradient descent and how it