Troubleshooting Python Application Development [Video]

More Information
Learn
  • Locate root causes by benchmarking and profiling your application
  • Speed up your code with natively Python idioms
  • Tackle long-running loops on big lists with NumPy
  • Speed up your I/O heavy tasks with concurrent programming
  • Make your apps run faster with parallel programming 
  • Organize your code better using Object Oriented Programming
About

Although you're comfortable with Python, you wonder whether you are writing fast and performant code. Once in a while, you run out of RAM or your application doesn't run fast enough, and this forces you to find a different solution.

To further your software development career, you need to understand why and how Python executes your code so that you can create clean code that compiles in time.

Troubleshooting Python Application Development is your answer. This course takes you through a structured journey of performance problems that your application is likely to encounter, and presents both the intuition and the solution to these issues. You'll get things done, without a lengthy detour into how Python is implemented or computational theory.

Quickly detect which lines of code are causing problems, and fix them quickly without going through 300 pages of unnecessary detail.

All the code and the supporting files of this course are available on GitHub at - https://github.com/PacktPublishing/Troubleshooting-Python-Application-Development

Style and Approach

The course is full of hands-on instructions, interesting and illustrative visualizations, and, clear explanations from a data scientist. It is packed full of useful tips and relevant advice. Throughout the course, we maintain a focus on practicality and getting things done, not fancy mathematical theory.

Features
  • Covers common Python application development problems documented online, leveraging sources such as Stack Overflow, Medium, and GitHub, and solves them entirely in one course.
  • Each video is constructed in a problem-solution format, making it easy to understand the problem and grasp the solution.
  • Tried and tested solutions to solve common problems, speeding up your Python code and reducing its memory footprint.
Course Length 2 hours 50 minutes
ISBN 9781788995337
Date Of Publication 30 Jul 2018

Authors

Rudy Lai

Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, machine learning, and Cloud computing.

Over the past few years, they have worked with some of the World's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways.
The company lives by its motto: Data -> Intelligence -> Action.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails for prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feed back into how our AI generates content.

Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first-hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye.

In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which you can learn about reinforcement learning and supervised learning topics in depth and in a commercial setting.

Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean's List, and received awards such as the Deutsche Bank Artificial Intelligence prize.