[FxpHD]Python Fundamentals for the Pipeline-TUTOR

[FxpHD]Python Fundamentals for the Pipeline-TUTOR
English | Size: 2.13 GB
Category: Tutorial

Taught by returning prof Michael Morehouse, PYT201 will explore the use (and, only occasionally, abuse) of Python in solving the fundamental problems of a VFX pipeline. Rather than focus on the various APIs of the dozens of proprietary and commercial packages you might encounter in your career moving from facility to facility, this course will emphasize the core fundamentals of building robust, efficient, well-documented and easily maintained modules and command-line tools that do the job well and do it often, and yet remain customizable enough to be empower future development as you build a library of useful tools. We will focus on keeping your code and skills as portable as possible, leveraging on the versatility of the core Python package and a few basic open source packages such as PyYAML. You will learn to document code using the Sphinx document generation system and ReStructured Text, and you will learn to check your good coding habits using Pylint. [Read more…]

Pluralsight – Introduction to Data Visualization with Python

Pluralsight – Introduction to Data Visualization with Python
English | Size: 219.53 MB
Category: CBTs

At the core of data science and data analytics is a thorough knowledge of data visualization. In this course, Introduction to Data Visualization with Python, you’ll learn how to use several essential data visualization techniques to answer real-world questions. First, you’ll explore techniques including scatter plots. Next, you’ll discover line charts and time series. Finally, you’ll learn what to do when your data is too big. When you’re finished with this course, you’ll have a foundational knowledge of data visualization that will help you as you move forward to analyze your own data. [Read more…]

Pluralsight – Introduction to Data Visualization with Python

Pluralsight – Introduction to Data Visualization with Python
English | Size: 219.53 MB
Category: CBTs

At the core of data science and data analytics is a thorough knowledge of data visualization. In this course, Introduction to Data Visualization with Python, you’ll learn how to use several essential data visualization techniques to answer real-world questions. First, you’ll explore techniques including scatter plots. Next, you’ll discover line charts and time series. Finally, you’ll learn what to do when your data is too big. When you’re finished with this course, you’ll have a foundational knowledge of data visualization that will help you as you move forward to analyze your own data.
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Pluralsight – NUKE Node Enhancement with Python

Pluralsight – NUKE Node Enhancement with Python
English | Size: 306.5MB
Category: CBTs

NUKE provides a rich collection of knobs to customize nodes. One of the most powerful custom knobs is the Python Script Button – A button that will execute any Python code when it’s clicked. In this course, NUKE Node Enhancement with Python, you’ll learn how to customize nodes using a variety of different knobs that execute Python code. You’ll be shown three practical examples that illustrate how to enhance and customize node functionality. First, you’ll discover how to create a custom camera node that can transform into a camera projection setup and back to a normal camera node with a simple button click.
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Functional Programming with Python


Functional Programming with Python
English | Size: 244 MB
Genre: eLearning

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Pluralsight – Working with Graph Algorithms in Python

Pluralsight – Working with Graph Algorithms in Python
English | Size: 219.09 MB
Category: CBTs

This course focuses on how to represent a graph using three common classes of graph algorithms – the topological sort to sort vertices by precedence relationships, the shortest path algorithm, and finally the spanning tree algorithms.
A graph is the underlying data structure behind social networks, maps, routing networks and logistics, and a whole range of applications that you commonly use today.
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Packtpub – Functional Programming in Python


Packtpub – Functional Programming in Python
English | Size: 597 MB
Genre: eLearning

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Lynda – Python Parallel Programming Solutions

Lynda – Python Parallel Programming Solutions
English | Size: 596.41 MB
Category: CBTs

Learn parallel programming techniques using Python and explore the many ways you can write code that allows more than one task to occur at a time. First, discover how to develop and implement efficient software architecture that is set up to take advantage of thread-based and process-based parallelism. Next, find out how to use Python modules for asynchronous programming. Then, explore GPU programming using PyCUDA, NumbaPro, and PyOpenCL. This course provides extensive coverage of synchronizing processes, streamlining communication, reducing operations, and optimizing code so you can select and implement the right parallel processing solutions for your applications. [Read more…]

Lynda – Learning Python with PyCharm

Lynda – Learning Python with PyCharm
English | Size: 398.90 MB
Category: CBTs

Learn Python programming with PyCharm, the cross-platform IDE that "takes care of the routine." Get your development environment set up correctly with instructor Bruce Van Horn’s step-by-step guidance, and explore PyCharm’s first-rate text editing tools. Learn how to improve your code quality with Lens Mode and Intentions, refactor and debug code, and perform unit testing with the PyCharm test runner. Then dive into working with SQL databases. Lastly, learn how to integrate Python with web projects that include HTML and JavaScript, and create a project with the Flask microframework. [Read more…]

Lynda – Introduction to Python Recommendation Systems for Machine Learning

Lynda – Introduction to Python Recommendation Systems for Machine Learning
English | Size: 177.73 MB
Category: CBTs

Discover how to use Python-and some essential machine learning concepts-to build programs that can make recommendations. In this hands-on course, Lillian Pierson, P.E. covers the different types of recommendation systems out there, and shows how to build each one. She helps you learn the concepts behind how recommendation systems work by taking you through a series of examples and exercises. Once you’re familiar with the underlying concepts, Lillian explains how to apply statistical and machine learning methods to construct your own recommenders. She demonstrates how to build a popularity-based recommender using the Pandas library, how to recommend similar items based on correlation, and how to deploy various machine learning algorithms to make recommendations. At the end of the course, she shows how to evaluate which recommender performed the best. [Read more…]