sushmitasivaprasad Goto Github PK

azure_ai_discovery

azureml-tutorial

classes

All class material

data-mining-project

House Price Prediction and Click Prediction Projects in Data Mining

datasharing

The Leek group guide to data sharing

human-activity-recognition-using-lstm-neural-networks-

The dataset consists of 10929 instances and 561 features, which is captured using an accelerometer and a gyroscope. The data is taken from 3-axial linear acceleration and 3-axial angular velocity data for 30 people performing static, dynamic and postural transitions . A Neural Network is built with 2 LSTM cells to classify the kind of activity the person is performing.

machine_learning_basics

Plain python implementations of basic machine learning algorithms

machinelearningnotebooks

Use the example notebooks in this repo to explore the Azure Machine Learning service.

markdown-here

Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.

natural-language-processing-

The polarity dataset from Cornell University consists of movie review documents which are labelled according to the overall sentiment of the rating as positibe or negative. The dataset consists of 1000 positive and 1000 negative review. The purpose of this model is to be able to correctly train and predict the sentiment of the movie review for the test dataset.

neural-networks

Implementation of the backward propagation algorithm using neural networks

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

python-tutorial-for-ipython

iPython tutorials for NLP, ML, AI in Python

sp17-i524

Class submissions for Spring 2017 i524

survival-analysis

A binary classification model was built using different classification algorithms to estimate the probability of a patient’s survival based on test results and symptoms. Achieved an F1 score of 82% using SVM classification model

transformers-for-nlp-2nd-edition

Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E and more