Pinned

No more confusion on Backpropagation

Backpropagation from scratch and handy — I always wanted to implement backpropagation on a simple network to understand its working. To be honest, I struggled for a week to implement it from scratch as I need to understand the flow of partial derivatives with the help of the chain rule before I step in. I wanted…

Deep Learning

11 min read

Deep Learning

11 min read

3 hours ago

Can RATINGS be given to articles in Medium with the help of RNN?

Why not MLP or CNN? Why RNN? Applications of RNN — I am thinking to pen down on RNN in brief. So, I thought of explaining the RNN concept using Medium articles examples. I would use the concept of MLP here. So, it would be useful to have a glance at the below resource. No more confusion on Backpropagation Backpropagation from scratch and handymvschamanth.medium.com Task To categorize the medium articles into Useful…

Data Science

4 min read

Can RATINGS be given to articles in Medium with the help of RNN?

Data Science

4 min read

Published in Innovations in Technology and Healthcare

·Dec 11, 2022

Ectolife (Artificial Womb) — Too dangerous if made real.

Destruction could be beyond the imagination, if not regulated. Is it life? or Creating a character in the video game? — I love technical innovations and I often feel fascinated, when I understand an innovation or idea. I had mixed feelings when I heard about Neuralink for the first time. I discussed it in my blog related to Neuralink. For the first time, I felt terrified by watching this Ectolife…

Technology

2 min read

Technology

2 min read

Dec 10, 2022

Optimizers are variants of Gradient Descent

When gamma = 1 → It has become an equally weighted value, where all the data points are having same weight at time t=3. When gamma = 0.5 → The most recent datapoint at time t=3 is x3 and it has the highest importance or most weight, whereas the x1…

Neural Networks

5 min read

Optimizers are variants of Gradient Descent

Neural Networks

5 min read

Dec 1, 2022

Gradient Descent is behind Machine Learning and Deep Learning

Gradient Descent is simple and basic for Deep Learning algorithms — Every Machine Learning and Deep Learning uses Gradient Descent or its variants, in backpropagation to find the best weights. But, then What is Gradient Descent? In order to understand the Gradient Descent algorithm better, there are a few concepts such as Slope and Maxima & Minima to be understood. Slope

Machine Learning

3 min read

Machine Learning

3 min read

Gradient Descent is behind Machine Learning and Deep Learning

Gradient Descent is simple and basic for Deep Learning algorithms

Every Machine Learning and Deep Learning uses Gradient Descent or its variants, in backpropagation to find the best weights.

But, then What is Gradient Descent?

In order to understand the Gradient Descent algorithm better, there are a few concepts such as Slope and Maxima & Minima to be understood.

Slope

Nov 27, 2022

Zero weight initialization on the layer with Relu activation fails miserably

Why does ‘zero’ weight initialization fail? What’s the optimized way? — The end goal of any Machine Learning and Deep Learning algorithm is about finding the best weights. which in fact is dependent on the Initialization of the weights —it is the starting step of finding the weights. What happens with Zero initialization? Let’s try to initialize a simple 1-layer network with all the weights to…

Neural Networks

6 min read

Zero weight initialization on the layer with Relu activation fails miserably

Neural Networks

6 min read

Nov 22, 2022

Backprop in CNN is too deep

Working of CNN from scratch (forward-prop and back-prop) — The first question that arose to my mind when I first heard about Convolutional Neural Networks is Why CNN when there is MLP? It is widely known that CNN is used for image data and they should be used while working on the images. MLP can also be used on the image data if we flatten…

Deep Learning

9 min read

Deep Learning

9 min read

Published in What-I-Say

·Nov 17, 2022

Time

This isn’t a mathematics blog. So, please don’t get carried away by the image. Integration means A method of adding or summing up the parts to find completeness in the limit of the scale. which means, if our aim is to reach Bangalore from Hyderabad (these are the limits…

Time

2 min read

Time

2 min read

Published in Chamanth MVS writes

·Oct 15, 2022

Hope — logic?

“HOPE” things should go fine “HOPEFULLY” you will be better “HOPING” for the best We can keep on writing many sentences on HOPE in such a way. In general, when we use the word HOPE — we use it in the context of FUTURE. But many times, we also heard…

Hope

2 min read

Hope

2 min read

Published in Witnessing in fighting the deadliest ……Wasn’t/Isn’t Easy

·Jul 26, 2022

CHAPTERS

Links for every chapter — Chapter — 1 : Initial Findings…..didn’t notice Chapter — 2 : Lockdown…….Locked me….. Chapter — 3 : Again…..Started Diagnosis Chapter — 4 : Doctor Consultation Chapter — 5 : Tests and hidden distress Chapter — 6 : Test Reports and Revelation Chapter — 7 : Panic attack and Chapter —…

Storytelling

1 min read

Storytelling

1 min read

No more confusion on Backpropagation

Can RATINGS be given to articles in Medium with the help of RNN?

Ectolife (Artificial Womb) — Too dangerous if made real.

Optimizers are variants of Gradient Descent

Gradient Descent is behind Machine Learning and Deep Learning

Gradient Descent is behind Machine Learning and Deep Learning

Gradient Descent is simple and basic for Deep Learning algorithms

Slope

Zero weight initialization on the layer with Relu activation fails miserably

Backprop in CNN is too deep

Time

Hope — logic?

CHAPTERS

Chamanth mvs