raamav Goto Github PK

bisectionsearch_example

Introductory yet interesting use-cases executed via Python

cs230-code-examples

Code examples in pyTorch and Tensorflow for CS230

cs61b

Data Structures and Algorithms | UC Berkeley

data-structures-and-algorithms-specialization-university-of-california-san-diego

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hangman-game

a version of the classic word-game

image-classification

Image Classification using Convolutional Neural Networks

image-color-segmentation

A tool which is able to segment images by colour, and identifies the top three colours present in the images

machinelearning_showcase

A collection of some of the interesting cases I have worked upon

mars-rover

OOP

ml-algo-numpy

ml_projects_1

Machine Learning Projects

natural-language-processing

Identifying Tweets Pertaining to Public Emergencies Using NLP (and other models on text-classification and sentiment analysis)

nlp-dl-pytorch

Collection of notebooks typical Natural Language Processing use-cases using Deep Learning (PyTorch Framework). Some of these notebooks are adapted/ inspired from what others have built (I have cited the original authors in such cases)

objectoriented_programming

some use cases

raamav.github.io

sentence2words

A basic sentence to words converter

sentiment-analysis-userreviews

Sentiment analysis on short and long form customer reviews. Extracting sentiment from Amazon Reviews (~100K short-form reviews) and IMDB Datasets (~50K long-form reviews)

standaloneprograms_python

simple yet interesting projects

templates

A compilation of useful templates

text-classification

Cases Include: Detecting & Categorising Toxic Comments on Social Media; Identifying Tweets pertaining to Natural Disasters (Micro-text Classification)

time-series-analysis

Forecasting Atmospheric CO2 and Forecasting Restaurant Visitors using classical (Holt-Winter's and ARIMA) and contemporary (RNNs and LSTMs) approaches