Machine Learning
Conteúdo de apoio sobre Machine Learning da disciplina de tópicos avançados em informática
Jupyter Notebooks
- Regressão Linear Simples, http://bit.ly/2KBTkUf
- Regressão Linear Múltipla, http://bit.ly/2nBOcGx
- MultiLayer Perceptron, http://bit.ly/2MI9kZQ
- SVM Linear, http://bit.ly/2Ov7vgh
- SVM RBF, http://bit.ly/2OBRHsk
Links Interessantes
- Excelentes tutoriais sobre aprendizado de máquina, https://matheusfacure.github.io/tutoriais/
- Tutorias de python e machine learning, https://github.com/cs-ufrn
- MLP para fins didáticos em C++, https://github.com/orivaldosantana/mlp
- colah's blog, http://colah.github.io/
- Deep Learning Book, http://www.deeplearningbook.org/
- Página web com lições sobre TensorFlow, https://learningtensorflow.com/
- Github sobre K Means Clustering de Siraj Raval, https://github.com/llSourcell/k_means_clustering/blob/master/kmeans.py.ipynb
Referências
- Livro Hands-On Machine Learning, https://github.com/ageron/handson-ml
- Super Data Science, https://www.superdatascience.com/machine-learning/
- Scikit-learn, http://scikit-learn.org/
- A Tutorial on Support Vector Machines for Pattern Recognition, https://www.di.ens.fr/~mallat/papiers/svmtutorial.pdf
Links de Dados
- Dados abertos UFRN, http://dados.ufrn.br/organization/ufrn
- Kaggle data sets, https://www.kaggle.com/datasets
Cursos Onlines
- Machine Learning - Udemy, https://www.udemy.com/machinelearning
- Deep Learning - Udemy, https://www.udemy.com/deep-learning-com-python-az-curso-completo
- Machine Learning - Google, https://developers.google.com/machine-learning/crash-course/
- Machine Learning - Coursera, https://www.coursera.org/learn/machine-learning
- Elements of AI, https://course.elementsofai.com/
Exercícios
- Implementação do perceptron, https://github.com/ect-info/ml/tree/master/guias/Perceptron
Bibliografia
- GÉRON; Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O’REILLY, 2017.
- MITCHELL; Machine Learning, Publisher: McGraw-Hill Science/Engineering/Math, 1997.
- NEGNEVITSKY; Artificial Intelligence: A Guide to Intelligent Systems, Second Edition, Publisher Addison Wesley.
- HAYKIN; Neural Networks and Learning Machines (3rd Edition), Publisher: Pearson.
- BISHOP; Pattern Recognition and Machine Learning, Springer, 2006.
- RUSSELL, STUART; NORVIG, PETER; Inteligência Artificial, 3. edição, Prentice Hall.
- BRAGA; CARVALHO; e LUDERMIR; Redes neurais artificiais: teoria e aplicações, 2007