Python News Tuesday, June 26
- 24 Best Python Courses, Books, and Online Tutorials 2018
- The Art of Deduction: featuring Pandas and Python – Towards Data Science
- Elegant solutions for everyday Python problems
- Face recognition with OpenCV, Python, and deep learning – PyImageSearch
- Top 10 Visual Studio Code extensions for Python development
Code, Python, Developer, node, nodejs
- How to Execute R and Python in SQL Server with Machine Learning Services
- Deep Learning Cheat Sheet (using Python Libraries)
- Python for Pentesters and Hackers « SecurityTube Training
- 8 Best SQL Courses Online To Advance Your Career
Career, AI, DataScience, DataScientist, BI
- Adnan’s Random bytes — Programming, Productivity,Entrepreneurship and Life Hacks
- Here isthe list some best Python courses,books, online tutorials, and certification programwill help you to become an expert in Python programming language and Python programmer.
- Thus we have organized the Best Python Courses, Books, Online Training, and Certification Programs which includes the Best Course, Product Description, Ratings, number of Students Enrolled as well as Products Image and a Call to Action to purchase the Courses from the respective learning platforms or websites for your convenience….
- Description: Learn to create Machine Learning Algorithms in Python and R from two Data Science experts.
- Description: The only Python course covering web, databases, web scraping, data science, web visualizations, image processing & more!
- If you dont like to take online courses and love reading books you can check out the below Learn Python The Hard way books series and other: – – Hope, these best Python courses, tutorials, and bookswill help you to become an expert in Python Language Programming.
@ileadgen: 24 Best Python Courses, Books, and Online Tutorials 2018https://t.co/2SF2twdk1E#Python #AI… https://t.co/wCKTeVkaCN
- Pandas comes with the following advantages which has made it the de facto standard in data analysis with Python: – Data Frame – Easy to read and write data in many tabular formats(CSV, Excel and even SQL) – Dealing with missing data – Easy to reshape data – Easy slicing…
- The standard notation of importing the pandas library is: – import pandas as pdImporting Data – There are several types of data file formats you can load in as a Pandas DataFrame.
- You can also use the head() function to print out the first 5 rows of your DataFrame(just to get a general idea of the kind of data or maybe the kind of values your columns the flip side, you can store your modified DataFrame into various formats too.
- Moving on!Selecting, Slice and various other data formatting operations: – Most of the select operations on DataFrame are very similar to the ones we perform on native python objects like Lists and Dictionaries.
- An entire column can be accessed in a following way using the dot in case we need a specific row of data from the selected column, we can use indexing in a similar way to select that specific that DataFrames follow the zero indexing formatWe can also use the iloc…
@fan_django: The Art of Deduction: featuring Pandas and Python☞ https://t.co/twCrc77uq7#Python #Pandas https://t.co/LreAQ92xrG
- In this article, we’ll examine three of those tools: magic methods, iterators and generators, and method magic.
- Using a Python shell, let’s say we’ve defined the costs for two food items in different currencies, like so: – – We could use magic methods to help instances of this class interact with each other.
- To make that a reality, we could implement the magic method on our class: – – Now we can use this class in a very intuitive way: – – When we add two instances together, we get a result in the first defined currency.
- For example, to access an item by index or key (in the case of a dictionary), use the method: – – Some magic methods even map to built-in functions, such as , which maps to .
- Let’s see it in action with a brief example: – – Let’s see how this method magic ties together in some sample code from a library I enjoy using called , which is a (poorly named) REST API client with transparent syntax that allows you to rapidly prototype any REST…
@opensourceway: 3 tools to make your #Python code more elegant, readable, intuitive, and easy to maintain: https://t.co/XKHf9tonLJ… https://t.co/axaIq3pS2c
@PythonWeekly: Face recognition with OpenCV, Python, and deep learning via @pyimagesearch https://t.co/jSYxxplHhX #python #opencv… https://t.co/UrNUgjp8Tk
- An extension with rich support for the Python language (including Python 3.6), including features such as linting, debugging, IntelliSense, code navigation, code formatting, refactoring, unit tests, snippets, and more!
- Visual Studio Code extension to quickly generate docstrings for python functions.
- The Anaconda Extension Pack is a set of extensions that enhance the experience of Anaconda customers using Visual Studio Code.
- It includes the following set of Visual Studio Code extensions: – – – – Highlight trailing spaces and delete them in a flash!
- This extension adds language colourization support for the Jinja template language to VS Code.
@BoostlogHQ: https://t.co/5FvZkqDp4q Top 10 Visual Studio #Code extensions for #Python development#Developer #node #nodejs… https://t.co/mH8cDDDjci
@analyticbridge: How to Execute R and Python in SQL Server with Machine Learning Services https://t.co/Pxd6jx5nNI
- This cheat sheet was produced by DataCamp, and it is based on the Keras library.
- Kerasis an easy-to-use and powerful library for Theano and TensorFlow that provides a high-level neural networks API to develop and evaluate deep learning models.
- For other cheat sheets covering all data science topics, click here.
@analyticbridge: Deep Learning Cheat Sheet (using Python Libraries) https://t.co/tyRRX724eO
@SecurityTube: Earn your #SPSE certification on your own time https://t.co/FNYuE2T6PP Learn attack task automation &… https://t.co/qWkFtijTUz
@ileadgen: 8 Best SQL Courses Online To Advance Your #Career https://t.co/jhdAUL7M6b #AI #DataScience #DataScientist #BI… https://t.co/lpgVpLYRGx
@realpython: Getting started with Apache Kafka in Python — https://t.co/hbAMCMkLVZ
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