My personal github repo for sharing code, theory, math’s and projects for training on all aspects of AI, ML, data science research for solving real world problems using classical supervised machine learning and Deep Learning Neural Net based models including Foundation LLM and multimodal models.

It contains sub repos by topic containing the code, theory and relevant documents.

1. DataScienceCourse - For classical supervised machine learning I would of course recommend my own course which is on Udemy, but I’ve put it all here for public use with theory and code a. I built this because most online courses lacked a good theoretical math’s foundation. Lots of code examples for every algorithm b. Python, Pandas, Statistics, Exponentials, Logarithm, Probability, Data Sampling c. Data Science Process – Problem, Wrangling, Algorithm Selection, Model Building , Visualization, Deployment, Data Wrangling d. Supervised Learning Algorithms – Regression, Classification, Clustering e. Model Persistence and Deployment, Deploying on AWS Cloud, Sagemaker, End 2 End Project 1 – Building a RoboAdvisor f. https://www.udemy.com/course/datascience-e2e-beginnerscourse-machinelearning-dataanalytics/
2. Neural Networks – ANN, RNN, DNN, BERT, Recommender systems and BERT from scratch using Keras, LSTM. NNs built from scratch using Pytorch numpy
3. LLM Foundation Models – Finetune LLM Llama, Mistral, Transformers, CUDA, Langchain, Huggingface, Supervised Fine Tuning, RLHF, Synthetic data, data annotation
4. NLP – LDA Topic modelling, Sentiment Analysis, Wordcloud, POS, ANN, XGB, Regression, LSTM, Feature Selection, tokenization, embedding, maths, spacy, nltk
5. Recommender Systems – from scratch using tensorflow, collaborative filtering, factorization, retrieval
6. Computer Vision – CNN, RNN, Transfer learning, Fully Connected NN, LSTM, Image classification, Object detection, Livestream, CIFAR10, MNIST, VGG16, YOLO, COCO. Models built from scratch using tensorflow keras numpy
7. Time Series Forecasting – ARIMA(X), SARIMA(X), VARMA(X), SES, acf, pacf, adfuller using statsmodels, maths, models
8. Synthetic Data Generation – using probability distribution sampling, regression, time series, numpy, random
9. Optimization – Formulation, excel solver examples a. Maximize demand/Minimize Production cost, Minimize Distribution Cost Meeting Trips and Truckload constraints, b. Minimize Purchase Admin Cost From Multiple Suppliers, Minimize Telcom Carrier Call Routing Cost with penalty, c. Minimize Travel Time from Hospital To District, Non Linear Minimize Distance from Fire Station to Town
10. Genetic Algorithm – Genetic selection, evolutionary search, classification model
11. Stacking – Vecstack for regression model stacking
12. Dimensionality Reduction – using PCA, LDA, classification
13. EDA – Detailed EDA using pandas, numpy, matplotlib, seaborn, Regression
14. Research papers – All the best papers (47) by Hinton, Lecun, Bengio et al on LLM, NN, DL, NLP, ML, CV, Transformers, BERT, etc
15. Sample Projects – Disease Prediction using Regression Synthetic Data
16. Other Projects – a. Robo Advisor Algo for building multi-asset portfolio using regression for forward predicted asset prices that uses historic& forecasted macroeconomic and central bank b. Predict monthly asset price (main stock indices, commodities, bonds) and direction (Higher/Lower) using macroeconomic data for US, UK and EU by applying regression algorithms c. US Fed FOMC Meeting minutes - Applying NLP algorithms to Predict Fed Fund Rates decision d. Some other regression related prediction algorithms

Hope this is useful for others in open source community. All work in progress, more updates as I finish learning and coding, especially multimodal models.

Courses: I’ve also listed some online courses I did from online platforms • Machine Learning A-Z: AI, Python & R o https://www.udemy.com/course/machinelearning/ • Deep Learning A-Z 2024: Neural Networks, AI o https://www.udemy.com/course/deeplearning/ • Data Science: Natural Language Processing (NLP) in Python o https://www.udemy.com/course/data-science-natural-language-processing-in-python • Natural Language Processing with Deep Learning in Python o https://www.udemy.com/course/natural-language-processing-with-deep-learning-in-python/ • Building Recommender Systems with Machine Learning and AI o https://www.udemy.com/course/building-recommender-systems-with-machine-learning-and-ai/ • Advanced AI: Deep Reinforcement Learning in Python o https://www.udemy.com/course/deep-reinforcement-learning-in-python/ • Deep Learning and Computer Vision A-Z + AI o https://www.udemy.com/course/computer-vision-a-z/