Sopan Kurkute's repositories
ams-ml-python-course
Machine Learning in Python for Environmental Science Problems AMS Short Course Material
Calculate-Precipitation-based-Agricultural-Drought-Indices-with-Python
Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).
climate_learn
Deep learning for climate modeling.
Machine-Learning-Climate-Parameterization
📈⛈️Machine learning-based parameterizations in climate models: a case-study on convection
Weed-Detection
This Problem is based on a Image Data set consisting of different types of weeds, to detect them in crops and fields. I have used Deep Learning Model called CNN(Convolutional Neural Networks) with Dropout, Batch Normalization, ReduceLearning rate on plateau, Early stoppig rounds, and Transposd Convolutional Neural Networks.
A-Beginner-Guide-to-Carry-out-Extreme-Value-Analysis-with-Codes-in-Python
A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.
AgroChain
Agricultural Supply Chain Dapp With Micro-Finance
Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)
climate-change-risk-analysis
Weighted overlay of climate change risk factors
climate-risk-insurances
The world's poor are being encouraged to take out insurance against climate-related disasters. But as the logic of some schemes unravels, those who profited least from fossil fuels are left paying for their damage.
ESMValTool
ESMValTool: A community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP
medium
for medium articles
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Python-Practical-Application-on-Climate-Variability-Studies
This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
scientific-python-lectures
Lectures on scientific computing with python, as IPython notebooks.
storm_forecast
Storm intensity forecasting using machine learning and RAMP distributed high computing environments
water
An auto machine learning for internet of things related to water systems.
Weed-Detector
Ai powered web app to detect weeds by analyzing crop and weed seedlings.