Python: Advanced Topics. #pythonchilla #pythonchilla #pythonkachilla2 #python #programming #ObjectOrientedProgramming

Julia is better than Python?. A thread 🧵. #python #pythonprogramming #pythonic #codanics #pythonchilla #pakdatasci #datascience

Ever got confused on what Graph/Chart to use on what occasion? Don't worry I've got you covered. A Thread 🧵👇. #codanics #python #datascience #pythonchilla #pythonprogramming #DataAnalytics #DataVisualization #pakdatasci #pythonkachilla2 #MachineLearning #visualization

Are you aware of "Walrus Operator"?.It's represented by ":=" a colon followed by the equal sign. It assigns and returns value at the same time. NOTE: It was introduced in Python 3.8. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2

Ever got confused on what Graph to use for Uni, Bi or Multi-variate analysis? Take a look. A Thread 🧵👇. #codanics #campusx #python #datascience #pythonchilla #pythonprogramming #DataAnalytics #DataVisualization #pakdatasci #pythonkachilla2 #MachineLearning #visualization

Ever wondered what "Regular Expressions" are?. They're simply a sequence of weird looking characters that specifies a search pattern in text. A Thread🧵👇. #python #codanics #pythonchilla #pythonprogramming #regex #programming #strings #Data #datascience #pakdatasci

We've all heard how Python makes coding easier. Here's one example of how you can turn a Minimum number finding function into an ~almost one-liner function. We call it the "Pythonic Method". #python #pythonprogramming #pythonic #codanics #pythonchilla #pakdatasci #datascience

The Zen of Python (PEP 20) is a set of nineteen aphorisms by Tim Peters that serve as guiding principles for Python’s design. A Thread 🧵👇. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2 #zenofpython #pep20

Useful Python Tricks: Part 2 🧵👇. 1- Unpacking.2- *Args (Arguments).3- **Kwargs (Keyword Arguments).4- *Args and **Kwargs.5- Lambda.6- Map.7- Filter.8- Reduce. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2

Useful Python Tricks 🧵👇. 1- Ternary Operators.2- List Comprehension.3- Enumerate Function.4- Zip Function.5- Default Dictionary.6- Merge Dictionaries.7- Match. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2

Data Visualization Libraries. When to use them? Here's a quick guide. #pythonkachilla2 #pythonkachilla #pakdatasci #DataScience #MachineLearning #datavisualization #codanics #pythonchilla #DataAnalytics

Automate feature selection by using:.1- mRMR.2- Boruta. Implementation:. #python #pythonchilla #codanics #campusx #machinelearning #artificialintelligence #FeatureSelection #featureengineering

Let’s Understand All About Data Wrangling!. A thread 🧵. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2.

DATA WRANGLING STEPS . A thread 🧵. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2.

Skill. If you want to become Data scientist. A thread 🧵. #python #codanics #pythonprogramming #DataScience #programming #pythonchilla #pythonkachilla2.

Optimal pythonic method for finding the minimum value. Code now works for numbers, strings (alphabetical), tuples, lists, sets and dictionaries (values). Thanks to Mr. Henk for improving it. #python #pythonprogramming #pythonic #codanics #pythonchilla

You can get more then 50K Dollar worth of recourses Free. Including (Canva, Unity, Namecheap, Atom, Digital Ocean, Git Co-pilot and many more ). #pythonchilla #pythonchilla #pythonkachilla2 #python #programming #ObjectOrientedProgramming. A Thread🧵.

Today, let's discuss a machine learning algorithm; "SUPERVISED ALGORITHM". In the 🧵👇, we'll examine its mathematical representation, example, and additional classification. #python #datascience #pythonchilla #DataAnalytics #pakdatasci #MachineLearning #codanics #EACADEMY

To get your Data Science project 💻off to the perfect start, let's quickly review the basic categories of machine learning algorithms. #python #datascience #pythonchilla #DataAnalytics #DataVisualization #pakdatasci #MachineLearning #visualization #codanics #EACADEMY

Did you know Giants like Google, Meta, Netflix etc. uses EDA to clean their data.#python #datascience #pythonchilla #DataAnalytics #DataVisualization #pakdatasci #MachineLearning .@aammar_tufail. #codanics.