You will anaylize a dataset of the global average sea level change since 1880. You will use the data to predict the sea level change through year 2050.
Global Average Absolute Sea Level Change, 1880-2014 from the US Environmental Protection Agency using data from CSIRO, 2015; NOAA, 2015. https://datahub.io/core/sea-level-rise
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
unipipeline simple way to build the declarative and distributed data pipelines. Why you should use it Declarative strict config Scaffolding Fully type
MidTerm Project for the Data Analysis FT Bootcamp, Adam Tycner and Florent ZAHOUI Hallo
First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin
Created covid data pipeline using PySpark and MySQL that collected data stream from API and do some processing and store it into MYSQL database.
Contents LDP LinUCB Description Model Architecture Dataset Environment Requirements Script Description Script and Sample Code Script Parameters Launch
VarDACAE This module is used to create Convolutional AutoEncoders for Variational Data Assimilation. A user can define, create and train an AE for Dat
GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian
Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.
ETL framework based on Yaml configs in Python A light framework for creating data streams. Setting up streams through configuration in the Yaml file.
PATC: Introduction to Big Data Analytics. Practical Data Analytics for Solving Real World Problems
Senator Trades Monitor This monitor will grab the most recent trades by senators and send them as a webhook to discord. Installation To use the monito
PyFunctional Features PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do
Lale is a Python library for semi-automated data science. Lale makes it easy to automatically select algorithms and tune hyperparameters of pipelines that are compatible with scikit-learn, in a type-
High Performance Molecular Dynamics Logging into CINECA's computer systems To logon to the M100 system use the following command from an SSH client ss
The Python Package for DataHerb A DataHerb Core Service to Create and Load Datasets.
Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc
ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.
Vaex-Big-Data-Analytics-for-Airline-data A Python notebook (ipynb) created in Jupyter Notebook, which utilizes the Vaex library for Big Data Analytics
A library to create multi-page Streamlit applications with ease.
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