sayanbanerjee32 Goto Github PK

automobile_complaint_analysis

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-projects-boilerplates

Boilerplates for mobile and web apps

awesome-sentiment-analysis

Repository with all what is necessary for sentiment analysis and related areas

awesome-text-summarization-1

The guide to tackle with the Text Summarization

bert-qa

BERT for question answering starting with HotpotQA

cdqa

An End-To-End Closed Domain Question Answering System.

cdqa-annotator

A web-based annotator for closed-domain question answering datasets with SQuAD format.

coreference-resolution

coursera-gen-ai-course-labs

cs224n-squad-project

danish_nlp

dash_on_flask

Dash on Flask with login_required (and application factory pattern)

dash_tutorial_series

Series of videos to cover important topics in Plotly Dash framework. Building an interactive app from scratch + cool tips and functionalities.

datasciencecoursera

datasharing

The Leek group guide to data sharing

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-reinforcement-learning

Repo for the Deep Reinforcement Learning Nanodegree program

deep-reinforcement-learning-for-boardgames

Third approach to Reinforcement Learning in Two Player games

deep-tic-tac-toe

A DDQN implementation in Tensorflow for solving the game of tic tac toe

dl-nlp-readings

My Reading Lists of Deep Learning and Natural Language Processing

dlaicourse

Notebooks for learning deep learning

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

extending-google-bert-as-question-and-answering-model-and-chatbot

BERT Question and Answer system meant and works well for only limited number of words summary like 1 to 2 paragraphs only. It can’t be able to answer well from understanding more than 10 pages of data. We can extend the BERT question and answer model to work as chatbot on large text. To accomplish the understanding of more than 10 pages of data, here we have used a specific approach of picking the data.

fastbook

Draft of the fastai book

feedback-prize-effectiveness

five-video-classification-methods

Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow

generative-ai-with-llms

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.

getting-cleaning-data-project

Getting and cleaning data course project

handson-ml

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