Practical-Data-Science-Blog

This repo contains friendly links for my medium blogs so you can read them without restirections. Also you can find them categorized with the codes so you can read more about the topics you are intersted in.

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Machine Learning Interview Questions & Answers for Data Scientists :octocat:
Deep Learning Interview Questions & Answers for Data Scientists :octocat:
Probability Interview Questions & Answers for Data Scientists :octocat:
Statistics Interview Questions & Answers for Data Scientists :octocat:
Python Interview Questions & Answers for Data Scientists :octocat:
SQL & Database Interview Questions & Answers for Data Scientists :octocat:
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Getting Started With Stable Diffusion :octocat:
Stable Diffusion-Based Image Generation Web Application Using Fast API & React :octocat:
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Overview of Computer Vision Tasks & Applications
Object Tracking with Particle Filters In Python :octocat:
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End-to-End Machine Learning Workflow Part 1
End-to-End Machine Learning Workflow Part 2
How To Split Data Effectively for Your Data Science Project :octocat:
Six Reasons Why Your Model Gives Bad Results
Brief Guide for Machine Learning Model Selection
Practical Guide to Support Vector Machine in Python :octocat:
Practical Guide to Boosting Algorithms In Machine Learning
Overview of Unsupervised Machine Learning Tasks & Applications
Practical Guide to Dimesnioality Reduction in Python :octocat:
Building Complex Models Using Keras Functional API :octocat:
A Quick Setup for Neural Networks Hyperparameters for Best Results
Building A Recurrent Neural Network From Scratch In Python
Machine Learning Models Are No Longer A Black Box
Step-by-Step Guide on Deploying Yolo3 Model on Fast API
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Manipulating Time Series Data In Python Pandas :octocat:
Time Series Analysis in Python Pandas :octocat:
Visualizing Time Series Data in Python :octocat:
Arima Models in Python Part 1 :octocat:
Arima Models in Python 2 :octocat:
Machine Learning for Time Series Data Regression :octocat:
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How To Write Python Clean Code
Write Efficient Python Code: Defining & Measuring Code Efficiency :octocat:
Write Efficient Python Code: Optimizing Your Code :octocat:
How To Eliminate Loops From Your Python Code :octocat:
Best Practices To Use Pandas Efficiently As A Data Scientist :octocat:
Stop Looping Through Pandas DataFrames & Do This Instead :octocat:
Selecting & Replacing Values In Pandas DataFrame Effectively :octocat:
How To Use .groupby() Effectively For Data Transformation As A Data Scientist :octocat:
20 Pandas Functions for 80% of your Data Science Tasks :octocat:
Data Exploration Becomes Easier & Better With Pandas Profiling :octocat:
Make Your Pandas Code 1000 Times Faster With This Trick :octocat:
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How to Read Machine Learning Papers Effectively
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Top 12 Practical Data Science Books
Top 12 Business for Data Science Books for Data Scientists
5 Non-Technical Books You Should Read As A Tech Worker
5 Top Data Cleaning and Feature Engineering Books For Data Scientists
10 Books To Become a Great Writer and Storyteller
5 Top Practical Computer Vision Books
5 Best Books To Learn Statistics And Probability For Data Scientists
3 Books To Build A Strong Deep Learning Foundation
This Book Will Learn You To Scale Deep Learning Models
The Best Book To Build A Strong Machine Learning Foundation
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Build Strong Deep Learning Foundations By Learning From Top Universities
Learn Reinforcement Learning from Top Universities
6 Top University Courses to Learn Mathematics for Machine Learning & Data Science
Learn Computer Vision From Top Universities
Learn AI from Top Universities Through these 10 Courses
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