My Background

 My name is Ans IMRAN.

 

Currently I am doing M1 in Physics ( Paris Physics Master ) from Sorbonne University and Universite Paris Cite. Sorbonne University is considered to be a very prestigious university in France.

In parallel, I am also enrolled in an online program in Artificial Intelligence. This program is in-part funded by Pakistani Government. It is run by PIAIC ( Presidential Initiative for Artificial Intelligence and Computing ).

So, right now, I am studying both Artificial Intelligence and Physics at a somewhat advanced level. After finishing my M2 in Physics and my online program in Artificial Intelligence, I'll decide whether I want to go for Physics or whether I want to go for AI.

On this blog I'll be sharing the decisions that I made and the things that I learned along the way!

Here is a link to my github repository. Here you can see some of the things that I have already learned. E.g: Python, Numpy, Pandas etc...

 

Wish me Bonne Chance!

Au Revoir!

Comments

Post a Comment

Popular posts from this blog

Ai SDK ui - 1 - Learning AI SDK UI with Next.js

I recently started learning AI SDK UI . I’ve been working with Next.js already, but this library adds something special. It's  framework agnostic !  It works with Angular, Vue, Svelte, and React. Of course, I’m doing it with Next.js (React) because that’s what I know best. One of the first things I tried was the useChat hook. This makes building a chatbot UI feel way simpler. Normally, handling messages, updating state, and keeping track of what the AI is saying can be messy. With useChat , a lot of that heavy lifting is done for you. Here are some cool things I noticed about it: Message streaming out-of-the-box. You don't need to implement manual streaming! The hook manages states like input, messages, status, and errors. You don’t need to write all that boilerplate yourself. I also liked that it handles more than just happy paths. For example: You can stop a response midway if you want. It provides it out of the box! There are even helpers for modifying message...
Read more

NMLS - 1. Clustering - Kmeans - Unsupervised Learning - Introductory Machine Learning

In 2022 I started the new  Machine Learning Specialization by Andrew NG. I completed it's first two courses in 2022. I'll sgare the jupyter notebooks from this specialization soon. Now, in 2023 when I am finally free from my M1, I am going to complete the specialization. Here is the first Assignment of course 3 (last course) on Clustering. Procedure : Distances between each data-point and all of the cluster centroids were computed The cluster centroid closest to the each data-point was assigned to that data-point The average positions of all of the data-points in a cluster were computed Corresponding centroids were moved to these new average positions The procedure was repeated for a specific number of iterations. Relevant  github link Relevant  video explanation (in Urdu)
Read more

NMLS - 3. Recommender Systems - Collaborative Filtering - Introductory Machine Learning

  In 2022 I started the new  Machine Learning Specialization by Andrew NG. I completed it's first two courses in 2022. I'll share the jupyter notebooks from this specialization soon. Now, in 2023 when I am finally free from my M1, I am going to complete the specialization. Here is the third Assignment of course 3 (last course) on Recommender Systems.   We were given a dataset which contained 'nu' users and 'nm' movies. The ratings that each user gave to various movies were present in the dataset. The task was: We have a new user who has not yet rated a lot of movies. We have have to recommended him movies based on his previous ratings.   Procedure : The cost function was implemented using For Loop & then without any loop (Vectorized Implementation) A list of movie ratings for a new user was created and was added to the training data The rows(movies) were normalized by taking average of each row for non-zero values and then subtracting each value from the...
Read more