Mathew K AnalyticsLearn seaborn with free notebooks
126 free video lessons that use seaborn, each with a downloadable Jupyter notebook and, where needed, the dataset. Learn seaborn by working through real examples.
12 minLesson 14
Beautiful Charts with Seaborn in Python | Data Analytics #14
32 minLesson 6
End-to-End Data Analyst Capstone
46 minLesson 1
Data Visualization for Beginners, with Matplotlib
45 minLesson 2
Data Visualization for Beginners, with Seaborn
17 minLesson 12
Understanding Demographic Variables in Market Research Analytics with Python
25 minLesson 24
Visualizing Survey and Market Data Using Python for Market Research
23 minLesson 25
Interpreting Patterns and Market Trends in Python Market Research Analytics
20 minLesson 26
Introduction to Market Segmentation: Essential Concepts for Market Research Analytics in Python
21 minLesson 30
Customer Clustering Using K-Means
26 minLesson 31
Statistical Thinking for Market Insights: Training for Data-Driven Decision Making
25 minLesson 32
Hypothesis Testing in Market Research: Essential Methods and Practical Python Analysis
22 minLesson 33
Comparing Groups Using t-Tests: A Practical Guide for Market Research Analytics in Python
25 minLesson 34
Chi-Square Tests for Analyzing Survey Relationships Using Python | Market Research Analytics
28 minLesson 35
Correlation and Key Driver Analysis in Market Research
25 minLesson 37
Measuring Customer Satisfaction with Market Research Data
27 minLesson 39
Master Brand Awareness & Perception Metrics Using Python for Market Research
22 minLesson 45
Visualizing Text-Based Market Insights in Python for Market Research
27 minLesson 47
Analyzing Market and Consumer Trends Over Time Using Python | Market Research Analytics
21 minLesson 48
Customer Cohort Analysis Training in Python for Market Research
24 minLesson 49
Retention and Churn Analysis Using Python for Market Research
27 minLesson 50
Introductory Market Trend Forecasting
24 minLesson 53
Data Storytelling for Stakeholders: Enhance Market Research Analytics Skills
27 minLesson 54
Best Practices for Market Research Visuals | Python Analytics Tutorial
24 minLesson 56
End-to-End Market Research Analytics Project
21 minLesson 57
Customer Segmentation Case Study Using Python for Market Research Analytics
24 minLesson 2
Installing Pandas and Setting Up Your Python Environment for Data Science Success
12 minLesson 3
Understanding Pandas Series and DataFrames: Essential Python Data Structures for Analysis
19 minLesson 8
Exploring and Cleaning Real-World Datasets with Python Pandas: A Practical Guide
22 minLesson 9
Hands-On With Pandas: Creating and Exploring DataFrames
24 minLesson 11
How to Identify and Handle Missing Data in Python Pandas for Accurate Data Analysis
17 minLesson 20
Master Filtering Rows and Columns in Pandas Using Query and isin for Data Analysis
20 minLesson 24
Master Lambda Functions & Vectorized Operations in Pandas for Faster Data Analysis
17 minLesson 32
Mastering Data Reshaping in Pandas with Melt, Stack, and Unstack Functions
12 minLesson 34
Mastering Dates and Times in Pandas for Effective Data Analysis
16 minLesson 35
Converting Strings to Datetime and Extracting Date Components Using Pandas in Python
15 minLesson 36
Mastering Time Series Analysis in Python: Resampling, Shifting, and Rolling Windows with Pandas
20 minLesson 38
Mastering Time-Based Grouping and Aggregations in Pandas for Effective Data Analysis
17 minLesson 46
Quick and Effective Data Visualization with Pandas plot() in Python
25 minLesson 47
How to Use Pandas with Matplotlib and Seaborn for Effective Data Visualization
17 minLesson 48
How to Create Line, Bar, Histogram, and Box Plots Using Python and Pandas
15 minLesson 49
Understanding Data Correlation and Heatmap Visualization Using Python and Pandas
36 minLesson 69
Comprehensive Pandas Tutorial in Python: Data Analysis from Beginner to Advanced
24 minLesson 24
Visualizing Retail Sales Data with Python for E-commerce Analytics
27 minLesson 41
Introduction to Machine Learning in Retail: Practical Training for E-commerce Analytics
16 minLesson 44
Predicting Customer Churn in Retail Using Python Analytics
23 minLesson 52
Designing Retail Analytics Dashboards with Python for E-commerce Insights
24 minLesson 24
Visualizing Content Performance
23 minLesson 25
Interpreting Content Trends and Patterns
27 minLesson 37
Thumbnail and Title Performance Analysis
29 minLesson 47
Analyzing Growth in Views and Subscribers
31 minLesson 48
Detecting Viral Spikes and Trends in Social Media Data
21 minLesson 54
Feature Importance for Engagement Prediction
26 minLesson 57
Designing Content Analytics Dashboards
29 minLesson 59
Best Practices for Visualizing Engagement Data
12 minLesson 42
2 - Seaborn- Countplot, Boxplot, Heatmap
25 minLesson 2
Setting Up Python Jupyter Notebooks for Probability and Statistics Analysis
7 minLesson 3
Understanding Data Types: Categorical, Numerical, Continuous, and Discrete Explained
15 minLesson 5
Measures of Spread Explained: Variance, Standard Deviation & Interquartile Range
14 minLesson 6
Fundamentals of Data Visualization: Histograms, Boxplots, and Scatterplots Explained
11 minLesson 7
Foundations of Probability: Understanding Events, Outcomes, and Sample Space
11 minLesson 8
Understanding Conditional Probability and Independence in Probability Theory
24 minLesson 9
Master Bayes Theorem: Real-Life Examples & Step-by-Step Probability Explained
9 minLesson 10
Understanding Bernoulli, Binomial, and Poisson Discrete Probability Distributions
14 minLesson 11
Understanding Continuous Probability Distributions: Uniform, Normal, and Exponential Explained
13 minLesson 12
Understanding Statistical Sampling and the Law of Large Numbers in Biblical Context
14 minLesson 13
Understanding the Central Limit Theorem: Key Concepts and Practical Applications
12 minLesson 15
Hypothesis Testing Explained: Concepts, Errors, and How to Interpret P-Values in Python
11 minLesson 16
Understanding t-Tests, Chi-Square Tests, and ANOVA in Python for Statistical Analysis
16 minLesson 17
Understanding Bootstrapping for Estimation and Confidence Intervals in Statistics
12 minLesson 18
Understanding Permutation Tests: A Flexible Approach to Hypothesis Testing
17 minLesson 19
Understanding Monte Carlo Simulations in Python for Statistical Modeling and Analysis
29 minLesson 21
Practical Applications of Simulation Techniques in Statistical Analysis and Decision-Making
13 minLesson 22
Understanding Covariance and Correlation: Pearson and Spearman Explained
12 minLesson 23
Simple Linear Regression in Python: Model Fitting & Interpretation Guide
11 minLesson 24
Understanding Multiple Linear Regression with Python’s Statsmodels Library
12 minLesson 25
Understanding Regression Diagnostics: Residuals and Key Assumptions Explained
10 minLesson 26
Practical Regression Project: Predicting Housing Prices with Python and Data Analysis
12 minLesson 28
Logistic Regression Explained: Master Coefficients & Odds Ratios Easily
14 minLesson 29
Master Accuracy, Precision & Recall for Evaluating Classification Models in Python
12 minLesson 30
Understanding ROC Curves and AUC for Evaluating Classification Models in Python
24 minLesson 34
Understanding Bayesian Statistics: Foundations of Priors and Posteriors Explained
15 minLesson 35
Bayesian Estimation Explained: Using SciPy and PyMC for Practical Inference in Python
21 minLesson 36
Practical Applications of Bayesian Inference: Step-by-Step Examples and Analysis
19 minLesson 38
Hypothesis Testing Explained: Applying Statistical Methods to Real-World Data
12 minLesson 40
Comprehensive Time Series Forecasting Project: From Data Preparation to Deployment
34 minLesson 41
Comprehensive Statistical Analysis: Step-by-Step Capstone Project Case Study
10 minLesson 14
Introduction to Seaborn for Data Visualization with Built-in Python Datasets
11 minLesson 15
Understanding Distribution Plots in Python: Histogram, KDE, Violin, and Box Plots Explained
11 minLesson 16
Visualizing Categorical Data in Python with Seaborn: Bar, Count, and Swarm Plots
14 minLesson 17
Understanding Relationship Plots in Seaborn: Scatter, Regression, and Pairplot Explained
13 minLesson 18
Understanding Heatmaps and Correlation Matrices with Seaborn for Data Analysis
10 minLesson 19
Mastering Custom Themes and Aesthetics in Seaborn for Clear Data Visualization
19 minLesson 4
Building a News Data Scraping and Analysis Project Using Python
21 minLesson 10
Comprehensive Airbnb Data Analysis Using Python for Biblical Stewardship Insights
18 minLesson 11
Comprehensive Analysis and Visualization of Global Covid-19 Data Using Python
22 minLesson 15
Analyzing and Predicting Iris Flower Species Using Data Science Techniques
23 minLesson 17
Building a Car Price Prediction Model Using Python and Data Science Techniques
20 minLesson 20
Analyzing Uber Trips Data: A Step-by-Step Guide to Data Science Techniques
18 minLesson 26
Predicting Wine Quality with Machine Learning: A Step-by-Step Guide Using Python
25 minLesson 27
Building Accurate Disease Prediction Models with Machine Learning: A Step-by-Step Guide
23 minLesson 29
Predicting Heart Disease with Logistic Regression: A Step-by-Step Python Guide
27 minLesson 36
Online Payment Fraud Detection Using Machine Learning in Python | Data Science Project
24 minLesson 38
Building and Training Handwritten Digit Recognition Models with Scikit Learn
26 minLesson 40
Building a Credit Card Fraud Detection System with Machine Learning Techniques
20 minLesson 41
Building a Recommendation System in Python: A Step-by-Step Guide for Beginners
23 minLesson 49
Deep Learning for Wine Type Classification: Step-by-Step Model Training Guide
22 minLesson 51
Building a Neural Network for Handwritten Digit Recognition: A Step-by-Step Guide
24 minLesson 53
Logistic Regression for Handwritten Digit Recognition Using PyTorch: Step-by-Step Tutorial
13 minLesson 76
4 - Loan Default Prediction - Risk Modeling
19 minLesson 77
Predicting House Prices with Regression Using the Ames Housing Dataset
22 minLesson 1
Understanding Data Mining and the Knowledge Discovery in Databases (KDD) Process
22 minLesson 2
Data Mining vs Data Science vs Machine Learning: Key Differences Explained
13 minLesson 5
Fundamentals of Exploratory Data Analysis and Visualization for Biblical Data Insights
17 minLesson 6
Data Cleaning Fundamentals: Managing Missing Values, Noise, and Outliers in Datasets
13 minLesson 10
Essential Data Preprocessing Techniques Using Titanic and Iris Datasets in Python
16 minLesson 13
Understanding Histograms, Scatterplots, and Heatmaps for Data Visualization
26 minLesson 16
Understanding Decision Trees: ID3, C4.5, and CART Algorithms for Classification
23 minLesson 22
Customer Churn Prediction: Step-by-Step Python Tutorial Using Real Data
17 minLesson 31
Understanding AdaBoost and XGBoost: Key Boosting Techniques in Machine Learning
23 minLesson 11
Handling Missing and Dirty Operations Data
22 minLesson 38
End-to-End Supply Chain Analytics Project
20 minLesson 30
Fundamentals of Time Series Analysis for Banking Professionals Using Python
21 minLesson 31
Analyzing Transaction Trends and Seasonality in Finance Using Python
23 minLesson 32
Applying Moving Averages and Smoothing Techniques to Financial Time Series in Python
23 minLesson 50
Seasonal Patterns in Financial Markets: Understanding Recurring Trends
22 minLesson 57