Pinned Repositories
Airbnb_project
Descriptive analysis of Airbnb data from Seattle, Boston and Copenhagen
airline-ranking
This is a brief Insights on causes of flight delay based on Viz and implementation of Airline carrier ranking system based on data of flights to and from Texas ( Bureau of Transportation ) during Jan 2017. Using PandaSQL ( SQL+ Python)
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
Audio-Sentiment-Analysis
This repository consists of work done to analyse sentiment of a customer in a conversation with a call center agent using various machine learning algorithms and audio features.
audio_emotion_analysis
The library is useful for analyzing the emotions present in any audio file(call/music/recordings) into three classes namely positive, negative, neutral.
augmented-neural-odes
Pytorch implementation of Augmented Neural ODEs :sunflower:
Automated-Resume-Screening-System
Automated Resume Screening System using Machine Learning (With Dataset)
awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
awesome-public-datasets
A topic-centric list of high-quality open datasets in public domains. New PR ☛☛☛
hummingbird
Hummingbird compiles trained ML models into tensor computation for faster inference.
100rabh1401's Repositories
100rabh1401/Airbnb_project
Descriptive analysis of Airbnb data from Seattle, Boston and Copenhagen
100rabh1401/amazon-sagemaker-examples
Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker
100rabh1401/augmented-neural-odes
Pytorch implementation of Augmented Neural ODEs :sunflower:
100rabh1401/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
100rabh1401/awesome-public-datasets
A topic-centric list of high-quality open datasets in public domains. New PR ☛☛☛
100rabh1401/basic_model_scratch
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library
100rabh1401/cloud-vision
Sample code for Google Cloud Vision
100rabh1401/data-analytics
Data analysis in python (and jupyter notebooks)
100rabh1401/Data-Science--Cheat-Sheet
Cheat Sheets
100rabh1401/DrDataScienceProjects
Code for projects shown on drdatascience.co.uk
100rabh1401/FreeML
A List of Data Science/Machine Learning Resources (Mostly Free)
100rabh1401/h2o-3
Open Source Fast Scalable Machine Learning Platform For Smarter Applications (Deep Learning, Gradient Boosting, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), ...)
100rabh1401/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
100rabh1401/inltk
Natural Language Toolkit for Indic Languages
100rabh1401/interpret
Fit interpretable models. Explain blackbox machine learning.
100rabh1401/medium
A collection of Medium posts
100rabh1401/ML
Codes related to various ML Hackathons
100rabh1401/news-graph
Key information extraction from text and graph visualization
100rabh1401/nltk
NLTK Source
100rabh1401/pandas-profiling
Create HTML profiling reports from pandas DataFrame objects
100rabh1401/predictive-model-on-watson-ml
Create and deploy a predictive model using Watson Studio and Watson Machine Learning
100rabh1401/PyConZA2018
Customer Segmentation
100rabh1401/ResumeParser
A framework to parse resumes, extract contact & other information, and check for required terms
100rabh1401/ResumeParser-1
Resume Parser using rule based approach. Developed using framework provided by GATE
100rabh1401/spam_detection
A Machine Learning Model to classify messages are spam or ham. Working app can be found at https://ehispamdetector.herokuapp.com/
100rabh1401/starbuck_capstone
An Udacity DSND Capstone - Starbucks Challenge
100rabh1401/Time-Series-Forecasting
100rabh1401/top10-mistakes-statistics-binder
100rabh1401/training
🐝 Custom Object Detection and Classification Training
100rabh1401/Twitter-Sentiment-Analysis-1
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization