Python Leftovers
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Traditional Face Detection With Python
Computer vision is an exciting and growing field. There are tons of interesting problems to solve! One of them is face detection: the ability of a computer to recognize that a photograph contains a human face, and tell you where it is located. In this course, you’ll learn about face detection with Python.
To detect any object in an image, it is necessary to understand how images are represented inside a computer, and how that object differs visually from any other object.
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What’s in a Name? Clarifying the Anaconda Metapackage
The name “Anaconda” is overloaded in many ways. There’s our company, Anaconda, Inc., the Anaconda Distribution, the anaconda metapackage, Anaconda Enterprise, and several other, sometimes completely unrelated projects (like Red Hat’s Anaconda). Here we hope to clarify two of those – the difference between the Anaconda Distribution and the anaconda metapackage.
The Anaconda Distribution is the installer that many people download to get a good start on a Python data science coding environment. It includes Python, pandas, scikit-learn, multiple data visualization options, and many other helpful libraries. This installer may come in the form of a GUI .pkg installer (for MacOS), a command-line .sh installer (for MacOS and Linux) and a GUI .exe installer (for Windows). When you see “Anaconda Distribution,” we’re referring to these installers.
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Getting Started with Machine Learning in the Enterprise
Machine learning (ML) is a subset of artificial intelligence (AI) in which data scientists use algorithms and statistical models to predict outcomes and/or perform specific tasks. ML models can automatically “learn from” data sets to improve their performance.
ML is uniquely applicable to enterprise business use cases across a wide number of industries — for example, credit scoring and fraud detection in financial organizations, and tumor detection and DNA sequencing in healthcare. Given the wide applicability, it’s no surprise that many in the enterprise have already embraced machine learning. According to Deloitte Insight’s 2018 survey of US-based early adopters, 63% were already using ML in their enterprise organizations.
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Organizing PythonPune Meetups
One thing I like most about meetups is, you get to meet new people. Talking with people, sharing what they are doing helps a lot to gain more knowledge. It is also a good platform to make connections with people having similar area of interests. I have been attending PythonPune meetup since last 2 years. In this blog post, I will be sharing some history about this group and how I got involved in organizing meetups. I will also cover all things involved in organizing a monthly meetup of PythonPune.
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Top 9 Django Concepts - Part 1: 4 Mins
When I first dive into Django after deciding to specialise as a Django developer.
The number of concepts that are required for anyone to learn to understand Django can be overwhelming.
Since Django development approach forces, you to develop in a single and opinioned way of web development with a vast ecosystem of packages to support your needs.
This could discourage potential Django developers, who prefer flexibility, a lesser amount of learning and unopinionated approach to develop a web application using Python.
These are the people who want to get things done by picking their own adventure using a smaller amount of packages instead of Django's batteries-included approach.
In the first part of the series, I will be covering only 3 concepts and their related technical terms to help you get up to speed in using Django.
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Stack Abuse: Using Django Signals to Simplify and Decouple Code
Systems are getting more complex as time goes by and this warrants the need to decouple systems more. A decoupled system is easier to build, extend, and maintain in the long run since not only does decoupling reduce the complexity of the system, each part of the system can be managed individually. Fault tolerance has also enhanced since, in a decoupled system, a failing component does not drag down the entire system with it.
Django is a powerful open-source web framework that can be used to build large and complex systems, as well as small ones. It follows the model-template-view architectural pattern and it is true to its goal of helping developers achieve the delivery of complex data-driven web-based applications.
Django enables us to decouple system functionality by building separate apps within a project. For instance, we can have a shopping system and have separate apps that handle accounts, emailing of receipts, and notifications, among other things.
In such a system, several apps may be need to perform an action when certain events take place. One event can occur when a customer places an order. For exmaple, we will need to notify the user via email and also send the order to the supplier or vendor, at the same time we can be able to receive and process payments. All these events happen at the same time and since our application is decoupled, we need to keep every component in sync, but how do we achieve this?
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