|17 days ago||5 days ago|
|GNU General Public License v3.0 only||OSI Approved|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
We haven't tracked posts mentioning karateclub yet.
Tracking mentions began in Dec 2020.
Will I be able to switch into a hardware job if my first job is in data science?
1 project | reddit.com/r/ElectricalEngineering | 7 Dec 2021
I can't tell you whether you'd like data science or machine learning, but I can tell you I took a class in it last year. It was an applied ML class targeting power systems engineers. ML is extremely statistics and probability heavy. I personally found the theory to be very dry, but the application to be rather enjoyable. We used sci-kit learn, which is an interesting Python package targeting academic data science and machine learning. https://scikit-learn.org/
Old guy programmer here, need to brush up on Python quickly!
13 projects | reddit.com/r/Python | 6 Dec 2021
scikit-learn for classical machine learning,
Data Science toolset summary from 2021
13 projects | dev.to | 13 Nov 2021
Scikit-learn - It is one of the most widely used frameworks for Python based Data science tasks. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Link - https://scikit-learn.org/
Intel Extension for Scikit-Learn
4 projects | news.ycombinator.com | 1 Nov 2021
Currently some works is being done to improve computational primitives of scikit-learn to enhance its overhaul performances natively.
You can have a look at this exploratory PR: https://github.com/scikit-learn/scikit-learn/pull/20254
This other PR is a clear revamp of this previous one:
Scikit-Learn Version 1.0
11 projects | news.ycombinator.com | 14 Sep 2021
Just to clarify, scikit-learn 1.0 has not been released yet. The latest tag in the github repo is 1.0.rc2
Top 10 Python Libraries for Machine Learning
14 projects | dev.to | 9 Sep 2021
Website: https://scikit-learn.org/ Github Repository: https://github.com/scikit-learn/scikit-learn Developed By: SkLearn.org Primary Purpose: Predictive Data Analysis and Data Modeling
where is binary_metric function in sklearn package
1 project | reddit.com/r/learnmachinelearning | 20 Aug 2021
There is a function named binary_metric in https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/metrics/_base.py
Use Scikit-Learn and Runflow
2 projects | dev.to | 6 Jul 2021
If you're not familiar with Scikit-learn and Runflow,
Confused as to what exaclty a piece of code does
1 project | reddit.com/r/learnmachinelearning | 18 Jun 2021
well you can start at https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/model_selection/_validation.py, or maybe someone will guide you later
What Makes Python Libraries So Important For Data Science Learning?
3 projects | reddit.com/r/u_Snoo36930 | 16 Jun 2021
Next comes the complexity of drawing the maximum possible number of valuable insights. Using different python libraries such as Scikit-Learn, PyTorch, Pandas, etc., complications of data analysis can be solved within a minute. And the complexity associated with visualisation gets handled by other data visualisation libraries like Matploitlib, PyTorch, etc.
What are some alternatives?
Keras - Deep Learning for humans
Surprise - A Python scikit for building and analyzing recommender systems
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tensorflow - An Open Source Machine Learning Framework for Everyone
gensim - Topic Modelling for Humans
TFLearn - Deep learning library featuring a higher-level API for TensorFlow.
MLflow - Open source platform for the machine learning lifecycle
seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit