Jaydeep Karale

youtube.com

In this video, we will be exploring the different ways to configure and store logging settings in Python. From using basic in-code configurations to more advanced methods such as JSON and YAML file storage, we will cover all the options available to you. We will also show you how to use the logging.config module to easily load and apply your configuration settings. Whether you're a beginner or an experienced developer, this video will provide valuable insights on how to effectively manage and store your logging configurations in Python. Don't miss out and watch now

|| Python Logging Part 4 || Implementing Filters & Adding Contextual Info using LoggerAdapter

- Objective tools 
- All about Shapes, Drawing tools, Typography & Fonts, Colors, Patterns
- Repeats, Vectorizing images, Recoloring 
- Logo design

Adobe Illustrator Essential

- What is photoshop for
- Workspace and layers and layer styles
-  Color modes, adjustment layers
- Shape, text, shadow
- Retouching & filters
- Transforms, distort and smart objects

Adobe Photoshop Essential

🐍 Python has rapidly grown to become one of the most used language in the tech industry. 

Objective Of This Path ?

The objective of this learning path is to share with the audience my journey, the path which I took, the resources(both free and paid) which I referred and continue to refer to this day. 

The course contains paid courses which offer high value and also corresponding free versions of the same topics. The advantage of 
paid courses is that they are updated from time to time so you always get access to the latest content.

Career Paths Which Python Opens Up ?
-- Backend Development
-- Data Analytics
-- Data Engineering
-- Data Scientist
-- Machine Learning & AI


How Is This Path Structured ?
-- Structured courses which teach everything about Python in single video
-- IDE Setup for Python(PyCharm, Jupyterlab, VsCode)
-- Managing virtual environments in Python using venv and miniconda
-- Individual video content for important Python concepts such as Decorators, Generators, Logging, Unit Testing, OOPs
-- Courses for Python Backend & Web Development covering Flask, Django & FastAPI
-- Courses for Python Data Engineering & Data Analysis covering Pandas, Numpy, Matplotlib, Seaborn
-- Courses for Python Data Science, Machine Learning/AI covering Pytorch, NLP and various machine learning concepts


Hope my journey & it's learning benefit anyone who takes this path.

|| Python Logging Part 4 || Implementing Filters & Adding Contextual Info using LoggerAdapter

Adobe Illustrator Essential

Adobe Photoshop Essential

Python Mastery: From Zero To Hero