Introduction to Data Science @ FGV
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:
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Related Courses cs109, cs229, ML Andrew Ng
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Data Science Concepts ref1, ref2, ref3, ref4, book1, book2, book3
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Model Selection ref1
- Feature Engineering ref1, book
- Automated Feature Engineering
featuretools
- Automated Feature Engineering
- Feature Selection ref1
- Hiperparameter Search ref1
- Cross Validation ref1, video1
- Oversampling and Undersampling ref1
- Regularization ref1, ref2
- Bias and Variance ref1
- Overfitting and Underfitting ref1
- Evaluation Metrics ref1, ref2
- Feature Engineering ref1, book
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Machine Learning Algorithms ref1, ref2, ref3, ref4, ref5, ref6
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Unsupervised ref1
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Supervised
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Linear Models ref1
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Bayesian Models
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k Nearest Neighbors (kNN) ref1
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Neural Networks and Deep Learning ref1, ref2, ref3, ref4, ref5, ref6, ref7, book, video, meme
- Convolutional Neural Networks ref1, ref2, ref3, ref4, ref5, ref6
- RNNs (Sequence Models) ref1
- Word Embeedings ref1, ref2
- Word2vec ref1, ref2, ref3, en-us trained models, pt-br trained models, ge-de trained models
- Doc2vec ref1
- Char2vec ref1
- Glove ref1
- LSTMs and GRUs ref1
- Reinforcement Learning ref1, ref2, ref3, ref4, ref5, ref6, programming resource
- Transfer Learning ref1, ref2
- Generative Adversarial Networks ref1, ref2, ref3
- Neural Network concepts
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Data Science Tasks
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Preparing the Environment
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Data Science and Visualization Tools
- Versioning Tools
- Exploratory Data Analysis Tools
- Machine Learning Tools
- NLP Tools
- Visualization Tools
- Big Data and Distributed computing
- Analytical Pipelines
- Other Tools
- Relational databases and SQL
- NoSQL Databases
- Elastic Search
- Graph Databases
- 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.