The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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Apache Superset is a Data Visualization and Data Exploration Platform
- superset
- apache
- apache-superset
- data-visualization
Data Apps & Dashboards for Python. No JavaScript Required.
Statistical data visualization in Python
Parallel computing with task scheduling
- dask
- python
- pydata
- numpy
common data analysis and machine learning tasks using python
- data-science
- python
- python-tutorial
- data-scientists
N-D labeled arrays and datasets in Python
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
- machine-learning
- scikit-learn
- statistical-learning
- xgboost
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
- pandas
- pandas-dataframe
- parallel-computing
- parallelization
CLI task management & automation tool
- python
- build-tool
- build-automation
- task-runner
Lightweight and extensible compatibility layer between dataframe libraries!
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Scalable machine 🤖 learning for time series forecasting.
- forecast
- forecasting
- machine-learning
- lightgbm
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
- pandas
- pandas-summary
- dataframes
- data-science
A web front-end for password cracking and analytics
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
- deep-learning
- agriculture
- pytorch
- dataset
BIA Bob is a Jupyter+LLM-based assistant for interacting with image data and for working on Bio-image Analysis tasks.
Visualize your shell usage with Highcharts!
- visualization
- highcharts
- bash
- web