Rank 4/125 MachineHack
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Updated
Jan 6, 2021 - Jupyter Notebook
Rank 4/125 MachineHack
BenchMetrics Prob: Benchmarking of probabilistic error performance evaluation instruments for binary-classification problems
Machine Learning with Python
January Hackathon of Machine Hack, involving Multi-class Classification Modeling, Advance Feature engineering, Optimizing Multi-Class log loss score as a metric to generalize well on unseen data.
Detect duplicate questions that have already been asked on Quora.
Basic machine learning neuron in pure ruby
Crop damage classification
My absolutely first Kaggle competition
Determining the class of cancer-causing mutations using text and genetic data
Create a machine learning model to help an insurance company understand which claims are worth rejecting and the claims which should be accepted for reimbursement.
Les bases du Deep Learning en Intelligence Artificielle.
An intro to tensorflow
load a dataset using Pandas and apply the following classification methods (KNN, Decision Tree, SVM, and Logistic Regression) to find the best one by accuracy evaluation methods (Jaccard, F1-score, LogLoss) for this specific dataset.
This repository has the implementation of Logistic Regression algorithm from scratch, using SGD (Stochastic Gradient Descent). Scikit Learn library is not used.
Identify American Express customers most likely to default in the next 3 months based on 190 anonymized transaction data features for over 500000 American Express customers.
We load a historical dataset from previous loan applications, clean the data, and apply different classification algorithms on the data.
This project is a famous example of machine learning. Thanks to the keras library, we have data of written diggits and the purpose is to train a ML algorithm in order to predict the correct output.
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