Vikas Singh's repositories
kaggle-Traffic-Congestion-Prediction
In this project, I am trying to predict traffic congestion, based on an aggregate measure of stopping distance and waiting times, at intersections in 4 major US cities: Atlanta, Boston, Chicago & Philadelphia.
Movies-Reviews-Bert-Sentiment-Flask-API
Fine-tune BERT for sentiment analysis. I have done text preprocessing (special tokens, padding, and attention masks) and build a Sentiment Classifier using the amazing Transformers library by Hugging Face! I have train my model on kaggle notebook on gpu. The model give the accuracy of 95.14% on validation dataset.
Toxic-comment-detector
Online Toxic Comment Detector web application: https://toxic-comment-detector.herokuapp.com/
Clickbait-News-Detector-With-XLNet-PyTorch-Inference
The project goal is to the classification of clickbait news and non-clickbait news. I have a fine-tune SOTA XLNet model for classification. I have used the amazing Transformers library by Hugging Face with PyTorch.
Data-Analysis-and-Visualization
This repository contains the data analysis and visualization projects on various datasets.
Simple-hacks-to-speed-up-your-Data-Analysis-in-Python
Some useful Tips and Tricks to speed up the data analysis process in Python.
VikasSingh-DS.github.io
creating a portfolio website.
kaggle-ASHRAE-Great-Energy-Comp
In this project, we have to develop accurate models of metered building energy usage in the following areas: chilled water, electric, hot water, and steam meters. The data comes from over 1,000 buildings over a three-year timeframe. With better estimates of these energy-saving investments, large scale investors and financial institutions will be more inclined to invest in this area to enable progress in building efficiencies.
awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
data-science-interviews
Data science interview questions and answers
Fake-JobPosting-Prediction-NLP
Created a classification model that uses text data features and meta-features and predict which job description are fraudulent or real.
kaggel-Categorical-Challenge-I
The project is to show complete exploration to understand the categorical data, technique of handing categorical variables and after it I will build a Machine Learning Model.
kaggel-Categorical-Challenge-II
This respositry contain codes of Categorical-Challenge-II. Baseline model achieve AUC score 0.78.
Kannada-MNIST
I choosed to build it with keras API (Tensorflow backend) which is very intuitive. Firstly, I will prepare the data (handwritten digits images) then i will focus on the CNN modeling and evaluation.
Practicing-ML
This repository contains practicing machine learning notebooks.
Predicting-House-Price-Advanced-Regression-Techniques
In this notebook, I extensively use plotly along with seaborn and matplotlib for data visualization and Machine learning Algorithms to 'predict house prices in Ames'.
titanic-classification-comprehensive-modeling
Using Classification Techniques, Data reprocessing, Feature Engineering, Feature Extraction and Classification Algorithms from Machine Learning to Predict who can Survive the attack of Tsunami. Data Description
Udemy-Data-Science-Bootcamp-Course
Learn data science with this awesome and simple bootcamp Course. This course contain various exercises with solution. Happy Learning