AjayK's starred repositories
CropYieldPrediction
This project aims to design, develop and implement the training model by using different inputs data. The machine will able to learn the features and extract the crop yield from the data by using data mining and data science techniques.
Yield-Prediction
:seedling: Crop Yield Prediction using Machine Learning
machine-learning
Content for Udacity's Machine Learning curriculum
Crop-Yield-Prediction-and-Estimation-using-Time-series-remote-sensing-data.
We aim to build an ML model that will predict the yield of a crop using time series analysis of remote sensing data.
Machine-Learning-in-R
Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles
matched_markets
Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.
asdar-book.org
data and scripts for the ASDAR book
deep-learning-from-scratch-pytorch
Deep Learning from Scratch with PyTorch
analyse-sales
Predicting customer renewal probability and optimizing sales agents time spent on each customer. This submission ranked top 4 percent in McKinsey Data Scientist hiring hackathon. LGBM, Scipy.
api-client
Gro Intelligence API Client
data-science-complete-tutorial
For extensive instructor led learning
lancaster-map
Creating beautiful road maps with 'osmdata' package in R
Intro_to_spatial_analysis
Intro to spatial analysis in R
CC_course_stream3
All the course materials for the "Mastering Modelling" stream of our online course
Crop-Yield-Prediction
Agricultural statistics and forecast are an important resource that the government has not explored commensurate to its impact. The aim of our project is to make this process computerized by implementing principles of data mining and analytics This Project will be research-based reports specifying these trends, studied and analyses from the data taken over past years. Actions to minimize the damage of drought will also be suggested.
Horticulture-Yield-Prediction-using-ARIMA
The autoregressive integrated moving average model, known as ARIMA model, helps to find the unique structure and patterns in data to make skillful forecast. This model is used to predict the yield of horticulture crops using R programming language.