Making machines think

Hi! I am Swarit Shukla a sophomore student studying Computer Science and Engineering with a specialization in AI & ML. My primary interest lies in NLP and NLP with reasoning. I am passionate about building useful applications of AI that people can actually use.

I also like to watch cinema. I know it sounds a bit childish, but I aspire to do great things and lead humanity forward lol :)

Projects

A collection of algorithms and models I've implemented from scratch to understand the math behind them.

• Neural Probabilistic Language Model Jupyter Notebook

  A character-level implementation of the MLP language model based on the paper 'A Neural Probabilistic Language Model' (Bengio et al., 2003).

• Bigram Language Model Jupyter Notebook

  A bigram character-level language model that predicts the next character in a sequence based only on the preceding character.

• Anomaly Detection from Scratch Python

  Writing an anomaly detection algorithm from scratch using only NumPy and Pandas to find outliers in datasets.

• Logistic Regression from Scratch Python

  Implementing all the underlying mathematical concepts behind logistic regression.

• Neural Network from Scratch Jupyter Notebook

  Implementation of a basic neural network model entirely from scratch utilizing NumPy and Pandas.

• Softmax Regression from Scratch Jupyter Notebook

  Implementing categorical cross-entropy and the advanced mathematical concepts behind softmax regression.

• Linear Regression from Scratch Python

  Showcasing how a linear regression model works with all the underlying mathematics involved.

• Stochastic Gradient Descent Python

  Using SGD in simple linear regression to calculate gradients using one target at a time instead of full batches.

• Multiple Variable Linear Regression Python

  Implementation of linear regression for multi-feature training sets.

Specializations & Courses

• Machine Learning Specialization — DeepLearning.AI

  Covered Advanced Learning Algorithms, Supervised Machine Learning, and Unsupervised Learning & Recommenders. [Certificate]

• Mathematics for Machine Learning and Data Science — DeepLearning.AI

  Mastery in Calculus, Linear Algebra, Probability, and Statistics applied to Machine Learning. [Certificate]

• Structuring Machine Learning Projects — DeepLearning.AI [Certificate]
• Improving Deep Neural Networks — DeepLearning.AI

  Hyperparameter Tuning, Regularization, and Optimization. [Certificate]

• Neural Networks and Deep Learning — DeepLearning.AI [Certificate]