🤖 💬 Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

Curate better data for LLMs

Code for the CVPR 2019 paper : Spectral Metric for Dataset Complexity Assessment

Customer Service Requests Analysis is one of the practical life problems that an analyst may face. This Project is one such take. The project is a beginner to intermediate level project. This repository has a Source Code, README file, Dataset, Image and License file.

code for generating a high-quality knowledge graph with metadata about datasets and links to publications

Using fuzzy cognitive maps for multivariate data forecasting in Python 3.8.

A web tool for local dataset browsing and processing developped using the Flask + Angular stack.

目标检测助手（ObjectDetectionAssistant）：分析数据集各类数量分布，BBox大小分布， BBox比率分布， BBox中心点分布；数据增强

PCA, Linear Regression, Multiple Linear Regression, Logistic Regression, Decision Tree, Random Forest

Blip 2 Captioning, Mass Captioning, Question Answering, and other tools.

A Machine Learning app created with Streamlit (https://www.streamlit.io/).

Files containing the project about passenger airline satisfaction.

Python scripts for analyzing the 'Top 250 IMDb TV Shows' dataset. Tasks include EDA, building a TV show recommendation system, sentiment analysis, IMDb rating prediction, and TV show clustering.

Test task from FutureComes

Analyzing dataset: https://github.com/pncnmnp/TIMDB

This project is towards the completion of the course COMP6321 - Machine Learning

Git for the Programming and scripting project 2020

Given an image query, the goal is to retrieve the relevant images from CIFAR-10 Dataset.

A repo for Project 1 of the OSU Bootcamp. This dataset analyzation project focuses on housing, incomes, and employment in the United States.

A simple project that creates a dataset of News Headlines with Primary Category, Secondary Category, Date, Day, Month,Year, Sentiment, SentimentPolarity, Emotion and Url. All News Headlines are scraped from punch newspaper and sorted into a csv file.