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 Modern Python LiveLessons: Big Ideas and Little Code in Python

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PostSubject: Modern Python LiveLessons: Big Ideas and Little Code in Python   Sun Apr 09, 2017 8:37 pm



Modern Python LiveLessons: Big Ideas and Little Code in Python
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 10Hours 40M | 27.8 GB
Genre: eLearning | Language: English
Modern Python LiveLessons: Big Ideas and Little Code in Python provides developers with an approach to programming in Python that expresses big ideas succinctly, with the minimum of code, allowing the business logic to shine through. It does so using a number of relevant examples from current problems, including data analytics and social media.


Modern Python LiveLessons: Big Ideas and Little Code in Python provides developers with an approach to programming in Python that expresses big ideas succinctly, with the minimum of code, allowing the business logic to shine through. It does so using a number of relevant examples from current problems, including data analytics and social media.

Description
In this video training, Raymond Hettinger starts by introducing modern Python foundational skills, tools, and techniques in the first half of the lessons. In the second part he shows you how to apply the tools and techniques to a real application.

Core skills of modern Python that enable you to elegantly code powerful solutions succinctly and efficiently:

How to use continuous and discreet functions in the random module, collections.Counter(), lambda, list operations, chained comparisons, and f-strings
How to use random.choice() and random.sample(); do resampling, bootstrapping, and significance testing; and run simulations
How to run static analysis on code with type hints and use static type checking
How to use defaultdict for grouping, key functions for data ordering, and zip* to transpose data, and how to flatten 2D data with multiple loops and list comprehension
How to use k-means to implement unsupervised learning
More defaultdict skills with which to pivot and accumulate data and reverse a one-to-many mapping
How to use sorted, bisect, and merge and how to conserve memory with string interning
How to normalize text and use the hashing tools in hashlib
How to use Bottle to build REST APIs and web applications
How to test using pytest, itertools, Hypothesis, pyflakes, mypy, and data validators










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