Amédée DERA's starred repositories
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
BayesianOptimization
A Python implementation of global optimization with gaussian processes.
activerecord-import
A library for bulk insertion of data into your database using ActiveRecord.
revise_auth
A pure Rails authentication system like Devise.
Data_Visualization
Mathematical, Statistics, Medical, Scientific Data Visualization
SuluFormBundle
Form Bundle for handling Dynamic and Symfony Forms in https://sulu.io
slog-quickwit
🚨 slog: Quickwit handler
GestionAnciensEtudiants
Petite application console en java pour la gestion des anciens diplômés.
symfony-ecommerce-formation
Projet contenant le code source de la formation "Création d'un site e-commerce sous symfony en 24H CHRONO"
Heart_Attack_Prediction_Model_with_Python
This Jupyter Notebook demonstrates the use of machine learning techniques to predict heart attack risks, highlighting the importance of accurate medical diagnostics. It navigates through data preprocessing, model training, and rigorous evaluation to select the most effective model based on recall.
Heart_disease_prediction
This project analyzes health data to predict heart disease. We explore, preprocess, and build ML models like KNN, SVM, Decision Trees, and Random Forest. Future plans include adding features, deploying in healthcare, and optimizing the model. Contributions welcome!
Heart_disease_prediction
This project analyzes health data to predict heart disease. We explore, preprocess, and build ML models like KNN, SVM, Decision Trees, and Random Forest. Future plans include adding features, deploying in healthcare, and optimizing the model. Contributions welcome!
Parkinson-s-Disease-Detection-
Analyzing Parkinson's disease detection from patient medical data utilizing Machine Learning algorithms such as SVM, GMM, Random Forest, KNN, and Modified KNN through accuracy comparison.
k-nearest-neighbor-python
L'algorithme kNN pour k-nearest neighbors ou k plus proches voisins est l'un des algorithmes les plus utilisés en Machine Learning + Hyperparameters Tuning.
Covid19-twitter-analysis
3 phase project that trains a classifier for covid-19 twitter data. (Bag-of-words, SVM, Feature Engineering)
heart-disease-project
This notebook looks into using various Python-based machine learning and data science libraries in an attempt to build a machine learning model capable of predicting whether or not someone has a heart disease based on their medical attributes.
Whatsapp-Covid-Fake-News-Detector
Implemented SVM, Naive Bayes\& LSTM logic using Tensorflow to detect fake news related to COVID-19 pandemic such as false government guidelines incorrect reporting of increase in cases, etc. LSTM showed accuracy of upto 80\% on a test size of 5000 samples where model was trained on 20,000 samples.
COVID19-Outcome-Prediction
🦠 COVID-19 Outcome Prediction: Discover if you'll recover or not! Dive into symptom-based insights and compare ML models. Will SVM outshine the rest?