lohith0501 Goto Github PK
Name: Lohith G N
Type: User
Company: Rakuten
Bio: Sr Data scientist (Mtech in Data science & engineering from BITS Pilani, PGPDM in Data science & Machine learning from University of Chicago)
Location: Bangalore
Name: Lohith G N
Type: User
Company: Rakuten
Bio: Sr Data scientist (Mtech in Data science & engineering from BITS Pilani, PGPDM in Data science & Machine learning from University of Chicago)
Location: Bangalore
Example showing how to generate a map with markers, custom markers, circle markers, vega visualizations, Geojson and choropleth maps
Search Your PDF App using Langchain, ChromaDB, Sentence Transformers, and LaMiNi LM Model. This app is completely powered by Open Source Models. No OpenAI key is required.
To understand time series there are many tests involved. Some of them are Augmented Dickey-Fuller Test which will let us know if data is stationary or non stationary. Second, Granger’s Causality Test.This test will help to conclude if there is any causality involved between variables. Eg: Y is caused because of X. Lastly, Durbin Watson Statistic.This test will let us know if there is any autocorrelation involved by looking into its residuals/lag residuals.
This effort was to check which kernals were the best performing for non linear data set. Comparison is for linear,RBF and Polynomial kernals.
Topic modeling is one of the way to extract keywords in a document. This can be primarily implemented using 3 methods such as LDA (Latent Dirichilet Allocation), NMF , LSI. Here i am using LDA for analyzing a text document and extracting its keywords. Here i have used pyLDAVis library for visualization which i felt is the best for visualizing LDA models.
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
Collection of all my code submissions for the Udacity intermediate Python course
This was an effort to cleanse the data using TF-IDF for text parsing and feature engineering
All my practice work on Django for building web apps for Machine learning.
These codes will help to extract data from websites
Word embedding is useful to create important features for vector representation. Here i have used word2vec model with skipgram model to train on sentences and represent them in vector space.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.