Mathew K Analytics
Welcome to this Youtube channel! I am a data scientist with a passion for helping others learn and grow in their careers. On this channel, you can expect to find a range of tutorials, resources, and insights related to the field of Data Science. Whether you are just starting out in the field or are an experienced professional looking to deepen your understanding, my content is designed to help you learn and succeed.
I have extensive expertise in areas such as Machine Learning, Predictive Analytics, Unsupervised Learning, Customer Analytics, Social Media Data Analytics, Business Intelligence and Analytics, Database Management, Statistical Programming using R, SAS, and Python, Data Visualization, and Market Research Analytics. I am always looking for new and innovative ways to apply my knowledge and skills to real-world problems, and I love sharing my insights and experience with others. Thank you for stopping by and I hope you find my content helpful and informative.
Building a KPI Dashboard with Pandas
Hands-on Project - Predicting House Prices
Scaling and Normalizing Data
Can You Learn Python and Data Science in One Video?
Encoding Categorical Variables
Preparing Data for scikit-learn Models
Освоение Pandas в Python: от основ до продвинутого анализа данных (полное руководство)
Feature Engineering with Pandas
Hands-on - Exploratory Data Analysis (EDA) Project
Building Interactive Visuals with Plotly and Pandas
Data Correlation and Heatmaps
Creating Line, Bar, Histogram, and Box Plots
Integrating Pandas with Matplotlib and Seaborn
Quick Visualizations using Pandas plot()
Working with MultiIndex and Hierarchical Columns_training
Hands-on - Optimizing Large Datasets in Pandas
Chaining Operations and Method Pipelines
Resampling, Shifting, and Rolling Windows_training
Categorical Data and Memory Optimization
Converting Strings to Datetime and Extracting Components_training
Advanced Slicing and Cross-Section Operations
Reshaping Data using melt, stack, and unstack_training
Time-based Grouping and Aggregations
Pivot Tables and Cross-tabulations
Multi-level Grouping and Custom Aggregations
Grouping Data with groupby() and Aggregations
Merging and Joining DataFrames (Inner, Outer, Left, Right)
Concatenating DataFrames Vertically and Horizontally
Hands-on - Data Transformation Challenge
Lambda Functions and Vectorized Operations