TODO
- The Seattle Real Estate Modelling exercice comes from https://towardsdatascience.com/machine-learning-data-insights-for-model-building-b6bdea0ac092
- Tensoflow Playground: https://playground.tensorflow.org/
- Data Science Contests: https://www.kaggle.com/
- imagenet: datasets of labeled pictures for training and testing models
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- Google Vision API: https://cloud.google.com/vision (no need to train or test, just send an image, also works for OCR).
- Zero To Deep Learning comes from https://github.com/Dataweekends/zero_to_deep_learning_video (and https://cloudacademy.com/search/?q=zero%20to%20deep%20learning)
- Deep Learning Maths Explained:
- 3Blue1Brown, chapter 1, intro: https://www.youtube.com/watch?v=aircAruvnKk
- 3Blue1Brown, chapter 2, gradient descent: https://www.youtube.com/watch?v=IHZwWFHWa-w
- 3Blue1Brown, chapter 3, backpropagation: https://www.youtube.com/watch?v=Ilg3gGewQ5U
- 3Blue1Brown, chapter 4, backpropagation calculus: https://www.youtube.com/watch?v=tIeHLnjs5U8
- AI as a Service: algorithmia.com, pepite.com
- GBM Model (Gradiant Boosting): https://towardsdatascience.com/understanding-gradient-boosting-machines-9be756fe76ab
- Azure Data Factory Pipeline: https://towardsdatascience.com/how-to-secure-your-azure-data-factory-pipeline-e2450502cd43
- https://www.kaggle.com/learn/overview
- AI free courses: https://www.forbes.com/sites/bernardmarr/2020/03/16/the-10-best-free-artificial-intelligence-and-machine-learning-courses-for-2020/#427069686f66
- How to spot a fake Data Scientist: https://towardsdatascience.com/from-sklearn-import-478c711dafa1
- Top 20 Data Sience interview questions: https://towardsdatascience.com/20-machine-learning-interview-practice-problems-3c86a572eeec
- Non-linearity of activation functions (secret of deep learning): https://fr.coursera.org/lecture/neural-networks-deep-learning/why-do-you-need-non-linear-activation-functions-OASKH
- XGBoost explained: https://www.youtube.com/watch?v=OQKQHNCVf5k
- Agile Artificial Intelligence (e-book for Pharo): https://agileartificialintelligence.github.io/ (ebook not available)
- ROC curve explained: https://machinelearningmastery.com/roc-curves-and-precision-recall-curves-for-imbalanced-classification/
- Python Libraries for ML: https://towardsdatascience.com/best-python-libraries-for-machine-learning-and-deep-learning-b0bd40c7e8c
- Choropleth Python Maps: https://towardsdatascience.com/a-beginners-guide-to-create-a-cloropleth-map-in-python-using-geopandas-and-matplotlib-9cc4175ab630
- Feature Selection in Machine Learning: https://towardsdatascience.com/feature-selection-in-machine-learning-d5af31f7276
- Deep Learning Algorithms Guide: https://towardsdatascience.com/deep-learning-algorithms-the-complete-guide-ce020bd47ecc
- K-fold Cross-Validation: https://machinelearningmastery.com/k-fold-cross-validation/
- Time Series Analysis with Python: https://towardsdatascience.com/time-series-analysis-with-theory-plots-and-code-part-1-dd3ea417d8c4
- Pandas Cheat Sheet: https://towardsdatascience.com/pandas-cheat-sheet-4c4eb6802a4b
- Generic Data Science Cheat Sheet: https://github.com/FavioVazquez/ds-cheatsheets
- Practical Statistics for Data Scientists: https://www.abebooks.com/9781491952962/Practical-Statistics-Data-Scientists-Essential-1491952962/plp
- Storytelling with Data (part 1): https://www.amazon.fr/Storytelling-Data-Visualization-Business-Professionals/dp/1119002257
- Storytelling with Data (part 2): https://www.amazon.fr/Storytelling-Data-Lets-Practice-English-ebook/dp/B07YZG2WR7/
- Azure Machine Learning: https://www.amazon.fr/Mastering-Azure-Machine-Learning-end-ebook/dp/B07R53PCZC/
- Data-Driven Science and Engineering: https://www.amazon.fr/Data-Driven-Science-Engineering-Learning-Dynamical/dp/1108422098 (youtube channel: https://www.youtube.com/channel/UCm5mt-A4w61lknZ9lCsZtBw)
- Data Science from Scratch (Python): https://www.amazon.com/Data-Science-Scratch-Principles-Python-ebook/dp/B07QPC8RZX
- Manipulation de données avec pandas, NumPy et IPython: https://www.amazon.fr/Analyse-donn%C3%A9es-Python-Manipulation-IPython/dp/2212141092
- An Introduction to Statistical Learning (with application in R): https://www.amazon.fr/Introduction-Statistical-Learning-Applications/dp/B00NBCM35O
- Analyse de données avec R: https://www.amazon.fr/Analyse-donn%C3%A9es-avec-Fran%C3%A7ois-Husson/dp/2753548692
- Statistiques avec R: https://www.amazon.fr/Statistiques-avec-R-Pierre-Andr%C3%A9-Cornillon/dp/2753519927
- The R Book: https://www.amazon.fr/Book-2Nd-Michael-J-Crawley/dp/8126569719
- Exploratory Data Analysis with R: https://www.amazon.fr/Exploratory-Data-Analysis-Roger-2016-04-20/dp/B01NGZSD38
- Microsoft Certified: Azure Data Engineer Associate needed exams:
- Microsoft Certified: Azure Data Scientist Associate needed exam:
- Designing and Implementing a Data Science Solution on Azure (DP-100)
- Microsoft Certified: Data Analyst Associate needed exam:
- Analyzing Data with Microsoft Power BI (DA-100)
- Microsoft Certified: Azure AI Engineer Associate needed exam:
- Designing an Azure AI Solution (AI-100)