Instructor: Renato Rocha Souza
This is the repository of code for the "Introduction to Data Science"
This class is about the Data Science process, in which we seek to gain useful predictions and insights from data. Through real-world examples and code snippets, we introduce methods for:
- data munging, scraping, sampling andcleaning in order to get an informative, manageable data set;
- data storage and management in order to be able to access data (even if big data);
- exploratory data analysis (EDA) to generate hypotheses and intuition about the data;
- prediction based on statistical learning tools;
- communication of results through visualization, stories, and interpretable summaries
Detailed Syllabus:
Related Courses cs109, cs229, ML Andrew Ng, free courses
Books ref1
Data Science Concepts ref1, ref2, ref3, ref4, book1, book2, book3
Model Selection ref1
- Feature Engineering ref1, ref2, book
- Automated Feature Engineering featuretools
- Feature Selection ref1, ref2, ref3
- Hiperparameter Search ref1
- Cross Validation ref1, video1
- Oversampling and Undersampling ref1
- Regularization ref1, ref2
- Bias and Variance ref1
- Overfitting and Underfitting ref1, ref2
- Evaluation Metrics and Explainability ref1, ref2, ref3, ref4, ref5, ref6, ref7
- Feature Engineering ref1, ref2, book
Machine Learning Algorithms ref1, ref2, ref3, ref4, ref5, ref6, ref7
- Unsupervised ref1
- Supervised
Linear Models ref1
Bayesian Models
k Nearest Neighbors (kNN) ref1
Neural Networks and Deep Learning ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10, simple implementation, book, viz, video, meme
- Deep Learning and NLP ref1
Neural Network concepts
- General Math
- Linear and dense layers
- Weight Initialization ref1, ref2
- Weight Averaging ref1
- Hyperparameter Tuning ref1, ref2
- Gradient Descent ref1, ref2, ref3, video
- Backpropagation ref1
- Loss Functions ref1
- Convolutional Neural Networks ref1, ref2, ref3, ref4, ref5, ref6, ref6, ref7, ref8, ref9, ref10, architectures, viz
- RNNs (Sequence Models) ref1, ref2, ref3
- Attention Models ref1
- LSTMs and GRUs ref1, ref2, ref3, ref4, ref5, ref6
- Word Embeedings ref1, ref2, ref3, ref4, ref5, ref6, ref6
- Word2vec ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref, video, en-us trained models, pt-br trained models, ge-de trained models, pre-trained models
- Char2vec ref1
- Sentence Embeddings ref1, ref2,
- Doc2vec ref1, ref2, ref3
- Beyond Word Embeddings ref1, ref2, ref3, ref4, ref5, ref6, ref7
- Glove ref1, ref2, ref3
- FastText ref1, ref2
- Misspelling Oblivious Word Embeddings (MOE) ref1, ref2
- Transformers ref1, ref2, ref3, ref4, ref5
- Reinforcement Learning ref1, ref2, ref3, ref4, ref5, ref6, programming resource
- Transfer Learning ref1, ref2, ref3, ref4, ref5, ref6, ref6, ref7
- Autoencoders ref1, ref2, ref3, ref4, ref5
- Generative Adversarial Networks ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, GANS and Deepfakes, Colab Notebooks
Data Science Tasks
NLP tasks ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10
- Text Classification ref1, ref2, model interpretability, pretrained models, other pretrained models
- Vector Representation ref1, ref2a, ref2b, ref3, ref4
- OCR ref1, ref2
- Topic Modeling ref1, ref2, ref3, ref4, ref5, ref5
- Text Mining and Information Extraction ref1, ref2, ref3, ref4, ref5
- Keyword Extraction and Text Summarization ref1, ref2, ref3, ref4, ref5, ref6, ref7
- Collocation Extraction ref1
- Text Generation ref1
- Regular Expressions ref1, ref2 , ref3
- Named Entity Recognition ref1, ref2, ref3, ref4, ref5, ref6, ref7
- Coreference Resolution ref1,
- Document and Sentence Similarity ref1, ref2, ref3, ref4
- Sentiment Analysis ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, ref10
- Sarcasm Detection ref1
- Chatbots ref1, ref2
- Labeling ref1, ref2
Graphs and Network Analysis ref1, ref2, ref3, ref4, ref5, ref7
Time Series Analysis ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8, ref9, video
Recommender Systems ref1, ref2, ref3, ref4, ref5, ref6, ref7, ref8
Music Classification ref1
Preparing the Environment
Versioning Tools
Exploratory Data Analysis Tools
Machine Learning Tools
NLP Tools
Visualization Tools ref1
Graph Analysis Tools
Dashboards and UIs
Neural Networks visualization
Relational databases and SQL
NoSQL / Graph Databases
Data Wrangling and Distributed computing
Analytical Pipelines
Machine Learning Datasets ref1
We are using https://git-lfs.github.com because the /datasets files can be large. Install it before the git clone.