I am an inquisitive being who loves mathematics and data, Takes an unconventional way to my problems, and is a jubilant character overall.
Looking at my obsession with mathematics and data, I have been working on machine learning for the past few months. The idea that we can make machines do human-level, intelligent tasks by using some simple mathematics behind it absolutely fascinates me.
Initially, I began with some simple linear regression and some simple classification and built a housing price predictor and MNIST handwritten data classifier too.
https://github.com/goyalpramod/MNIST_hand_written_classification
https://github.com/goyalpramod/Housing_price_predictor
This built a strong base for me to understand how feature engineering works and how cleaning the data is more important than actually making the model.
But the surface level interface of sklearn, which implemented the linear regression model on its own and never showed the beautiful maths behind it, didn't work well for me. So I learned how it was implemented using NumPy by scratch from Andrew Ng's lectures.
Later on, I switched my interests to neural networks. And it feels like I have been working on them for the longest time. Learning about CNNs, RNNs, and LSTMs has been joyful.
And I even built dogs vs cats classifier in Kaggle using CNNs.
https://www.kaggle.com/code/pramodgoyal/dogs-vs-cats-my-take/notebook