manojsubramanyam Goto Github PK

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

celebrity-death-analysis

A Kaggle's learning project to analyze Deaths of Celebrities in the past decade. This project is going to have lot of visualizations.

crewai-examples

crudepredictions

ML model to forecast crude oil..

datasciencer

a curated list of R tutorials for Data Science, NLP and Machine Learning

dmlm-research-and-production

document1

e-commerce-complete-flutter-ui

flutter-cheat-sheet

You need to get started quickly with Flutter? Here are some cheats that will help you build your next billion dollar app!!

flutter-course-resources

Learn to Code While Building Apps - The Complete Flutter Development Bootcamp

housing-regression-price-analysis

A Kaggle's learning project to develop a Regression model to predict Housing Prices.

human-activity-recognition

Ever wonder how a fitness band or a smart watch track your activity and show you summary of your day to day activity. Here in this repository we will go through one more application of our Machine learning.

ig-monitoring

IGMonitoring - Free, self hosted Instagram Analytics and Stats

instagramanalytics

A command-line based Python program that gets a user's Instagram analytics using Selenium and BeautifulSoup4, so no Instagram API Key is required.

machine-taster-classification

Problem Statement: Build a classification model which will classify the quality of wine depending on multiple factors and chemical composition of it. This is one of my academic projects to analyze the quality and give rating to wine using Machine learning and Data Science. Analysis like this will change how quality testing works. This kind of work greatly reduce expenses and thereby help to generate more profit.

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

sarcasticornot

Problem statement: Build Classification model to identify sarcasm. Given dataset includes tweets, tweet id and target variable (sarcastic/non- sarcastic). This is my major academic project. Here the data is unstructured and raw.

socially-x.github.io

startup_ng

This is google's tutorial

tensorflow-tutorials

TensorFlow Tutorials with YouTube Videos

tensorflow_tutorial

This is my understanding and learning of tensorflow x.x