Pinned Repositories
ANT-Truck-Data-Analysis
Analyzed extensive trucking data using Hadoop, pinpointing accident risk factors. Developed ETL workflows, analytics reports, and visualizations, aiding data-driven safety enhancements and addressing key factors for improved trucking safety.
Auto-Summarize-Articles
A NLP model that auto summarizes or produces an abstract of an article published in Washington Post.
Blog-App
A simple blog site made using node.js and mongodb(database).
Cat-Classifier-using-Vectorization
Binary classification of Cat using Logistic regression. Worked hard under guidance of Andrew Ng.
Classifying_Clothing_Images
Live-Face-Recognition-Tool
A tool that captures images and recognizes the person in the image through facial recognition system which is built using Facenet.
Movie_Search
A simple movie search webpage with no styling. Searches movie using Yahoo API.
Plant-Pathology-Disease-Detection
Developed an innovative plant pathology solution using image segmentation, object detection, and ensemble models to accurately identify leaf diseases. Leveraged AI techniques on leaf images, enabling precise disease diagnosis for improved agricultural yield.
Spotify-Data-Pipeline-for-Music-Analytics
Implemented Spotify's Music Analytics Data Pipeline leveraging AWS services: CloudWatch & Lambda for extraction, Lambda triggers for transformation, and AWS Glue, Athena, and crawlers for efficient data transformation.
StackExchange-Question-Tag-Classification
Developed a multilabel classification model for Stack Exchange tags using Pytorch with optimized hyper parameters and loss function for improved performance, to accurately label Stack Exchange Questions and enhance data analysis capabilities.
Sai-Prakash-R's Repositories
Sai-Prakash-R/Cat-Classifier-using-Vectorization
Binary classification of Cat using Logistic regression. Worked hard under guidance of Andrew Ng.
Sai-Prakash-R/ANT-Truck-Data-Analysis
Analyzed extensive trucking data using Hadoop, pinpointing accident risk factors. Developed ETL workflows, analytics reports, and visualizations, aiding data-driven safety enhancements and addressing key factors for improved trucking safety.
Sai-Prakash-R/Blog-App
A simple blog site made using node.js and mongodb(database).
Sai-Prakash-R/Classifying_Clothing_Images
Sai-Prakash-R/Live-Face-Recognition-Tool
A tool that captures images and recognizes the person in the image through facial recognition system which is built using Facenet.
Sai-Prakash-R/Movie_Search
A simple movie search webpage with no styling. Searches movie using Yahoo API.
Sai-Prakash-R/Patatap
A simple Patatap Website Clone.
Sai-Prakash-R/Regression-Model-with-Keras-to-predict-House-price
Sai-Prakash-R/Spotify-Data-Pipeline-for-Music-Analytics
Implemented Spotify's Music Analytics Data Pipeline leveraging AWS services: CloudWatch & Lambda for extraction, Lambda triggers for transformation, and AWS Glue, Athena, and crawlers for efficient data transformation.
Sai-Prakash-R/StackExchange-Question-Tag-Classification
Developed a multilabel classification model for Stack Exchange tags using Pytorch with optimized hyper parameters and loss function for improved performance, to accurately label Stack Exchange Questions and enhance data analysis capabilities.
Sai-Prakash-R/Titanic-Machine-Learning-from-Disaster---Kaggle
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.
Sai-Prakash-R/To-Do-List
A Webpage used to keep lists. Add and Delete experience is made smooth by Animations.
Sai-Prakash-R/Using-Databases-with-Python
My study and work in Coursera
Sai-Prakash-R/Using-Python-to-Access-Web
My study and work in Coursera
Sai-Prakash-R/Auto-Summarize-Articles
A NLP model that auto summarizes or produces an abstract of an article published in Washington Post.
Sai-Prakash-R/Plant-Pathology-Disease-Detection
Developed an innovative plant pathology solution using image segmentation, object detection, and ensemble models to accurately identify leaf diseases. Leveraged AI techniques on leaf images, enabling precise disease diagnosis for improved agricultural yield.
Sai-Prakash-R/Theme-Labeling-of-Articles
A NLP model that gives the theme of a particular article