Skip to content
#

scikit-learn-python

Star

Here are 89 public repositories matching this topic...

Language: All
Filter by language
All 89 Jupyter Notebook 48 Python 25 HTML 6 R 3 Svelte 1
Sort: Most stars
Sort options
Most stars Fewest stars Most forks Fewest forks Recently updated Least recently updated

flo7up / relataly-public-python-tutorials

Star 132

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

python twitter-bot data-science machine-learning reinforcement-learning deep-learning time-series neural-network recurrent-neural-networks feature-selection openai neural-networks stock-price-prediction churn-prediction keras-tensorflow stock-market-prediction time-series-prediction time-series-forecasting scikit-learn-python openai-api
  • Updated Aug 9, 2023
  • Jupyter Notebook
Machine-Learning-with-Scikit-Learn-Python-3.x

reddyprasade / Machine-Learning-with-Scikit-Learn-Python-3.x

Star 51

In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dimensional entry (aka multivariate data), it is said to have several attributes or features. Learning problems fall into a few categories: supervised lea…

python machine-learning reinforcement-learning vector scikit-learn sklearn machine-learning-algorithms scikit-image regression prediction consists supervised-learning classification semi-supervised-learning python-3 unsupervised-learning scikit-model scikit-learn-api scikit-learn-python
  • Updated Jun 16, 2021
  • Jupyter Notebook
Machine_Learning

Lawrence-Krukrubo / Machine_Learning

Star 7

Machine learning is the sub-field of Computer Science, that gives Computers the ability to learn without being explicitly programmed (Arthur samuel, American pioneer in the field of Computer gaming and AI , coined the term Machine Learning in 1959, while at IBM )

python tensorflow linear-regression supervised-learning logistic-regression clustering-algorithm knearest-neighbor-algorithm classification-algorithm unsupervised-machine-learning scikit-learn-python
  • Updated Dec 14, 2020
  • Jupyter Notebook

UtsavMurarka / MXene-machine-learning

Star 5

Classification of MXenes into metals and non-metals based on physical properties

machine-learning deep-learning neural-network random-forest physics scikit-learn sklearn machine-learning-algorithms logistic-regression machinelearning atoms decision-trees molecules scikitlearn-machine-learning atomic-physics sklearn-classify knn-classifier sklearn-library machinelearning-python scikit-learn-python
  • Updated Oct 19, 2020
  • Jupyter Notebook
IEEE-ECG-Ensemble-XGBoost

souvikmajumder26 / IEEE-ECG-Ensemble-XGBoost

Star 3

👨‍💻 Developed AI Models - Ensemble of Random Forest & SVM and XGBoost classifiers to classify five types of Arrhythmic Heartbeats from ECG signals - published by IEEE.

python data-science machine-learning random-forest numpy svm scikit-learn pandas python3 xgboost ensemble-learning matplotlib support-vector-machine svm-model ensemble-model svm-classifier scikitlearn-machine-learning ensemble-classifier ensemble-machine-learning scikit-learn-python
  • Updated Jun 22, 2023
  • Jupyter Notebook

dpscience / DMLLTDetectorPulseDiscriminator

Star 2

DMLLTDetectorPulseDiscriminator - A supervised machine learning approach for shape-sensitive detector pulse discrimination in lifetime spectroscopy applications

machine-learning scikit-learn detector artificial-intelligence discriminator high-energy-physics materials-science time-of-flight scikitlearn-machine-learning lifescience fluorescence-microscopy-imaging positron-emission-tomography supervised-machine-learning pulse-detection gaussian-naive-bayes-implementation lifetime-spectroscopy positron-lifetime-spectra fluorescence-correlation scikit-learn-python pulse-shape-discrimination
  • Updated Jan 20, 2021
  • Python

AshishPandey88 / Nanda-Devi-Glacier-Loss

Star 2

Feburary 7,2021 Ecological Disaster (Nanda Devi Glacier, IND: 7,108 m above sea level). Satellite image analysis using the methodology of image segmentation shows that the Glacier cover in Nanda Devi has substantially decreased over the last 4 decades. It has gone down from 43% in Year 1984 to 20% in Year 2022 (in relation to the captured area i…

image image-processing scikit-image spatial-analysis satellite-imagery image-segmentation climate-model climate-science climate-change glaciers scikit-learn-python glacier-modelling
  • Updated Mar 23, 2023
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the scikit-learn-python topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the scikit-learn-python topic, visit your repo's landing page and select "manage topics."

Learn more