Mısra Turp
Here is where we learn! This is a space to take it slow and understand the most important data science and machine learning concepts, hands-on where applicable.
My aim is to break down the complex topics into understandable chunks and teach it in a way that does not overwhelm the viewers. We grow together as a community of learners. Feel free to ask questions, request new videos and leave comments with your feedback.
See you in there!
Making Your Project Presentable: Last Touches for an Impressive Portfolio
Bonus lesson: Turning a Regression Problem into a Classification Problem
Is your model actually that good? Validating Machine Learning Models
Improve Machine Learning Model Performance with Tuning
Step-by-Step Preparing and Training a Machine Learning Model
Feature Engineering: Integrate a new data source into your dataset
Feature Engineering: Create new features using existing data
The Basics of Evaluating Machine Learning Projects
How to Train a Benchmark Model for your Machine Learning Project
Problem Definition and Data Preparation for a Real-Life Data Science Project
Extract Hour, Day, Month Info from Pandas DateTime
Fixing Incorrect Column Types in Pandas to Prepare Data for ML
Data Cleaning after Identifying Data Problems in Pandas
Data Exploration: Identifying Data Issues and Their Potential Causes
Using Data Visualization to Identify Data Problems
How Collecting Data Works on a Real-Life Data Science Project
Creating a GitHub Repository for a Data Science Project
Introduction to Jupyter Notebooks: explore the main functionalities
How to Set up a Data Science Development Environment
Hands-on Data Science course: Let's build a project together from scratch!
Key Concepts and Techniques for Natural Language Processing
How are training and tuning different?
Python vs. R comparison (by a die-hard Python fan)
Data Visualization Libraries For Python
Why do we split data into train test and validation sets?
How to fix missing values in your data
Quick explanation: One-hot encoding
How to Implement CNNs in Keras
CNN follow along calculations
Basics of Convolutional Neural Networks