**************** Machine Learning **************** Articles & Tutorials #################### `Skills for ML `_ `Jupyter Notebook Server with AWS EC2 and AWS VPC `_ `The 5 Clustering Algorithms Data Scientists Need to Know `_ `The Complete Life Cycle of Data: From Exploration to Deployment `_ `Data augmentation `_ `In praise of the autoencoder `_ `Up and Running with AWS EC2, S3, Linux and Deep Learning `_ `Cupy documentation `_ `Accuracy, Precision, Recall & F1 Score: Interpretation of Performance Measures `_ `AI Meets a 96 Years Old NGO: Improving Case Management for Cross-Border Child Protection - How can AI help alleviate social workers’ administrative burden `_ `Using Machine Learning to Solve Real-World Problems `_ `Deploy a Model Using Docker as Endpoint and Pathology Mobile App `_ `Using Machine Learning to Predict Country Population `_ `Naives Bayes in sci-kit learn Naive Bayes: `_ `Random forest in sci-kit learn Random Forest: `_ `How to build a chrome extension `_ `Predicting energy demand with neural networks `_ `From Streamlit to Heroku `_ `Time Series forecasting using Auto ARIMA in python `_ `SHAP `_ `Gaussian Process Forecasting Web Tool `_ `Time Series Nested Cross-Validation `_ `ARUNDO `_ `How to Deploy a Streamlit App with Heroku `_ `Anomaly Detection Techniques in Python `_ `Forecasting Energy Consumption using Machine Learning and AI `_ `Predicting Solar Energy Production with Machine Learning `_ `Dataquest Tutorial `_ `Deploying Dashboards for Machine Learning with AWS `_ `Predicting smart grid stability with deep learning `_ `Time Series Nested Cross-Validation with sklearn `_ `Time Series Analysis — A quick tour of Prophet `_ `How to Predict Solar Energy Production `_ `An Introduction to Missing Data in Clinical Trials `_ `Guide to Encoding Categorical Features Using Scikit-Learn For Machine Learning `_ `Semi-supervised approach article `_ `How to accelerate DevOps with Machine Learning lifecycle management `_ `8 tactics to combat imbalanced classes in your machine learning Dataset `_ `MLJAR Automated Machine Learning for Humans `_ `Using Causal Inference: How Can AI Help People Slow Their Aging Down `_ `Using Predictive Modeling: A Data Driven Approach To Impact Investment Strategies `_ `Mia Tutorial: Machine Learning Model Deployment on Mia `_ `"To find optimal Model for implementing a decision making system to `_ Research Papers ############### `Tackling Climate Change with Machine Learning `_ `Machine Learning for Conservation Planning in a Changing Climate `_ `Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data `_ `Deep Clustering for Mars Rover image datasets `_ `Crop yield prediction using machine learning `_ `Data Science for Weather Impacts on Crop Yield `_ `Semantic segmentation of crop type in Africa `_ `Support Vector Machine Accuracy Assessment for Extracting Green Urban Areas in Towns `_ `Unsupervised Learning for Image Classiffication `_