Edit me

Below you can find the topics in which we have organized the content. You can access by either the Topics dropdown menu at the top, or by clicking in topics icons.

-Topics marked with 🆘 icon require contributors to add content.

-Topics with 🚧 icon are under construction and need contributors to edit the content.

INTRODUCTION TO DATA SCIENCE

📊 Introduction to Data Science 🚧 🐍 Introduction to Python 🆘 Introduction to R 🆘
🐚 Introduction to the UNIX shell (Bash) 🐘 SQL 🤠 Data Wrangling 🚧
🤝 Data Sharing 🆘 ℹ️ Information Theory 🆘 ✋ Suggest a topic

NATURAL LANGUAGUE PROCESSING

🦜 Introduction to NLP 🆘 📠 Machine Translation 🚧 ✉️ Semantic Vectors 🚧
💌 Sentiment Analysis 🆘 💬 Speech Prediction 🆘 🗣️ Speech Recognition 🆘
🟠 Topic Models 🆘 🔡 Word2Vec 🚧 ✋ Suggest a topic

CLASSIFICATION AND REGRESSION

🏁 Introduction to Kernel Methods 🚧 📉 Introduction to Regression 🆘 📏 Logistic and Multinomial Regression 🆘
👶 Naive Bayes 🆘 🌲🌲 Random Forest 🚧 🌫️ Support Vector Machines
⚔️ Cross Validation 🎗️ Lasso Regression 🚧 🎲 Ridge Regression 🚧
📈 Splines 🆘 ✋ Suggest a topic ✋ Suggest a topic

MODEL FITTING AND REGULARIZATION

🔧 Introduction to Model Fitting 🆘 🦄 Linear Mixed Effects Models 🥅 Elastic Nets 🚧
🧑🏿‍🎓 Semi-supervised Learning 🆘 👩🏽‍🏫 Supervised Learning 🚧 👨🏿‍🎓 Unsupervised Learning 🚧
🕵️ Agent-based Modeling 🚧 ✋ Suggest a topic ✋ Suggest a topic

TOOLS FOR DATA SCIENCE

🧰 Introduction to Tools for Data Science 🆘 🐱 Git 🆘 🐙 GitHub 🚧
🪐 Jupyter Notebooks 🍃 Overleaf 🥭 Papaja 🚧
📓 R Markdown 🛠️ Reproducibility Tools 🚧 🐚🛠️ Shell tools 🆘
🕸️ Web Scraping 🆘 ✋ Suggest a topic ✋ Suggest a topic

DATA REDUCTION

🙏 Introduction to Data Reduction 🆘 🔩 Eigen Decomposition 🚧 🟢 K-means 🆘
🏘️ K-nearest Neighbours 🆘 🟣 Locally Linear Embeddings 💈 Principal Component Analysis
👻 Spectral Clustering 🗼 Singular Value Decomposition 🆘 🎎 t-Stochastic Neigbour Embeddings 🆘
✋ Suggest a topic ✋ Suggest a topic ✋ Suggest a topic

NEURAL NETWORKS

🆘
🕸️ Introduction to Neural Networks 🤪 Activation functions 🚧 🌊 Backpropagation Algorithm 🚧
👁️ Convolutional Neural Networks 🆘🎭 Generative Adversarial Networks 🚧 🔁 Long Short Term Memory Networks 🆘
🏗️ Working with Prebuilt Networks 🆘 🔁 Recurrent Neural Networks 🦾 Transformer Models 🆘
🛺 Variational Autoencoders 🆘 🐶 Image Classification 🚧 ✋ Suggest a topic

CATEGORIZATION AND INFERENCE

🗠 Introduction to Statistical Inference 🆘 🔔 Gaussian Mixture Models 🚧 🌽 Kernel Density Estimation 🆘
💓 Latent Dirichlet Allocation 🆘 ✋ Suggest a topic ✋ Suggest a topic

REINFORCEMENT LEARNING

🐶 Introduction to Reinforcement Learning 👩🏿‍🎤 Actor Critic Models 🆘 🎰 Contextual Multi-Armed Bandits 🆘
🕸️🐶 Deep Hierarchical Reinforcement Learning 🚧 🕹️ Dyna Q Algorithm 🆘 🎰 Multi-armed Bandits 🆘
🎲 Monte Carlo Search 🚧 🗺️ Model Based RL 🆘 🥕 Model Free RL 🆘
🎛️ Policy Search 🆘 🕰️ Temporal Difference Learning 🆘 🌳 Tree Based Monte Carlo Search 🚧
✋ Suggest a topic ✋ Suggest a topic ✋ Suggest a topic

TIME SERIES

⌛ Introduction to Time Series 🆘 📉 Cross Wavelet Analysis 🆘 💹 Detrended Fluctuation Analysis 🆘
🌀 Kalman Filter ↩️ Recurrence Quantification Analysis 🚧 ✋ Suggest a topic

NETWORK AND GRAPHS

🌐 Introduction to Networks and Graphs 🆘 🌎 Small World Structure 🆘 ☋ Node Degree 🆘
🧿 Node Centrality 🆘 🧠 Network Science for Brain Networks 🆘 🖧 Modularity in Graphs and Networks 🆘
🖇️ Graph Layout Algorithms 🆘 🧑🏻‍🤝‍🧑🏻 Community Structure in Graphs and Networks 🆘 🌌 State Space Modeling 🚧
⭕ Graph Partitioning 🆘 🗄️ Graph and Network Data Structures 🆘 ✋ Suggest a topic

MISCELLANEOUS

🌐 Structured Query Language ✋ Suggest a topic ✋ Suggest a topic