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Saket-Kr / ML-Prep

Star 5

A repo holding the implementation as well as some theoretical explanation of the important relevant concepts. It is going to be in development for a long long time. I'll keep adding things everytime I have something to add to it, and I have the time for it. One can use it to learn the basics of Machine Learning from kind of scratch.

linear-regression regression linear reinforcement-learning-algorithms recall logistic-regression variance gradient-descent learning-algorithms bias mini-batch supervised-machine-learning unsupervised-machine-learning logistic-regression-algorithm bias-variance-trade recall-precision
  • Updated Oct 2, 2021
  • Jupyter Notebook

felipexw / guessb

Star 4

Webapp para classificar comentários (positivos, negativos e neutros) advindos do Facebook usando Natural Language Toolkit (NLTK) + Django e Bootstrap na interface Web.

bootstrap random-forest django-rest-framework nltk logistic-regression knn decision-tree-classifier gradient-boosting nltk-library multinomial-naive-bayes knearest-neighbor-classifier knn-classification logistic-regression-algorithm id3-algorithm gaussian-naive-bayes-implementation nltk-data nltk-python bernoulli-naive-bayes
  • Updated Apr 23, 2021
  • Python

Jspano95 / Retail-Customer-Classification-Modelling

Star 3

Classification ML models for predicting customer outcomes (namely, whether they're likely to opt into email / catalog marketing) depending on customer demographics (age, proximity to store, gender, customer loyalty duration) as well as sales and shopping frequencies by department

feature-engineering decision-tree-classifier support-vector-classifier voting-classifier logistic-regression-algorithm random-forest-classifier customer-segmentation knearest-neighbor-classification classification-models consumer-insights xgboost-classification
  • Updated May 4, 2021
  • Jupyter Notebook

sauriii98 / Deep-Learning-algorithms

Star 3

Implementation of all basic algorithms needed in Deep Learning

deep-neural-networks deep-learning cnn neural-networks deep-learning-algorithms optimization-methods residual-networks optimization-algorithms binary-classification cnn-model basic-algorithm logistic-regression-algorithm initialization cnn-classification gradient-check cat-notcat-classification logistic-regression-using-nn regularization-methods
  • Updated Jan 27, 2019
  • Jupyter Notebook

Sarthak-Mohapatra / Classification-of-tumors-in-Human-Breast-as-Bening-or-Malignant-using-ML-Algorithms.

Star 3

As part of this project, I have used Machine Learning (classification) algorithms for classification of tumors in Human Breasts as Non-Cancerous/ Benign or Cancerous/ Malignant tumors.

python random-forest rstudio svm exploratory-data-analysis jupyter-notebook feature-selection neural-networks normalization logistic-regression-algorithm backward-elimination svm-kernel cancer-prediction
  • Updated May 13, 2020
  • Jupyter Notebook

Sarthak-Mohapatra / Building-Algorithm-from-scratch-for-prediction-of-Average-GPU-run-time-and-classifying-the-run-type.

Star 2

As part of this project, I have developed algorithms from scratch using Gradient Descent method. The first algorithm developed will be used to predict the average GPU Run Time and the second algorithm will be used to classify a GPU run process as high or low time consuming process.

gpu rstudio matrix linear-regression exploratory-data-analysis machine-learning-algorithms threshold prediction convergence classification gradient-descent regression-models classification-algorithm logistic-regression-algorithm regression-algorithms classification-model experimentations error-curves train-test-error algorithm-from-scratch
  • Updated Aug 4, 2020
  • R

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