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Пройти курс от Гарварда CS109
Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.
Критерий завершения
Все лекции просмотрены, все задания сделаны
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Неделя 1
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Лекция 1 Course Overview
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Неделя 2
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Lab 1: Pandas, Python, and Github
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Lecture 2: Web Scraping. Regular Expressions. Data Reshaping. Data Cleanup. Pandas
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Lecture 3: Exploratory Data Analysis
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Неделя 3
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Lab 2: Scraping, Pandas, Python, and viz
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Lecture 4: Pandas, SQL, and the Grammar of Data
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Lecture 5: Statistical Models
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Неделя 4
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Lab 3: Probability, Distributions, and Frequentist Statistics
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Lecture 6: Story Telling and Effective Communication
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Lecture 7: Bias and Regression
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Неделя 5
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Lab 4: Regression, Logistic Regression: in sklearn and statsmodels
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Lecture 8: More Regression
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Lecture 9: Classification. kNN. Cross Validation. Dimensionality Reduction. PCA. MDS.
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Неделя 6
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Lab 5: Machine Learning
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Lecture 10: SVM, Evaluation.
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Lecture 11: Decision Trees and Random Forests
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Неделя 7
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Lab 6: Machine Learning 2
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Lecture 12: Ensemble Methods.
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Lecture 13: Best Practices
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Неделя 8
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Lab 7: Ensembles
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Lecture 14: Best Practices, Recommendations and MapReduce
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Lecture 15: MapReduce Combiners and Spark
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Неделя 9
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Lab 8: Vagrant and VirtualBox, AWS, and Spark
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Lecture 16: Bayes Theorem and Bayesian Methods
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Lecture 17: Bayesian Methods Continued
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Неделя 10
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Lab 9: Bayes
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Lecture 18: Bayesian Methods Continued,Text Data
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Lecture BONUS: Interactive Visualization
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Неделя 11
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Lab 10: Text and Clustering
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Lecture 19: Clustering
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Lecture 20: Effective Presentations
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Неделя 12
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Lab 10: Projects, and an example
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Lecture 21: Experimental Design
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Lecture 22: Deep Networks
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Неделя 13
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Lecture 23: Guest Lecture: Building Data Science
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Lecture 24: Wrapup, and where to go from here.
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- 21 сентября 2018, 17:49
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