Machine Learning

General Setup

• Create Virtual Environment using “virtualenv” and add it to Jupyter Notebook
• Create Virtual Environment using “conda” and add it to Jupyter Notebook
• 7 ways to load external data into Google Colab

Data Analysis

Pandas

• Reading & Writing data
  • 4 tricks to parse date columns with Pandas read_csv() | 📙 Notebook
  • Pandas read_csv() tricks you should know | 📙 Notebook
  • All Pandas read_html() you should know for scraping data from HTML tables | 📙 Notebook
  • How to convert JSON into a Pandas DataFrame? | 📙 Notebook
  • Pandas json_normalize() for flattening JSON | 📙 Notebook
• Data Profiling
  • 9 Pandas value_counts() tricks | 📙 Notebook
  • Getting more value from the Pandas count() | 📙 Notebook
• Data Preprocessing
  • What is One-Hot Encoding and how to use get_dummies() | 📙 Notebook
  • Working with missing values in Pandas | TBA soon
  • Working with datetime in Pandas DataFrame | 📙 Notebook
  • 11 Tricks to Master sort_values() in Pandas | 📙 Notebook
  • How to do a Custom Sort on Pandas DataFrame | 📙 Notebook
  • Pandas cut() to transform numerical data into categorical data | 📙 Notebook
  • Pandas qcut() for binning numerical data based on sample quantiles | 📙 Notebook
  • Finding and removing duplicate rows in Pandas DataFrame | 📙 Notebook
  • Renaming columns in a Pandas DataFrame | 📙 Notebook
  • 10 tricks for Converting data to a numeric type | 📙 Notebook
  • 10 tricks for Converting numbers and strings to datetime | 📙 Notebook
  • Pandas resample() tricks for manipulating time-series data | 📙 Notebook
  • When to use Pandas transform() function | 📙 Notebook
  • Difference between apply() and transform() in Pandas | 📙 Notebook
  • Introduction to Pandas apply(), applymap(), and map() | TBA soon
  • All the Pandas shift() you should know | 📙 Notebook
  • Delete rows/columns from a DataFrame using drop() | 📙 Notebook
• Combining data
  • All the Pandas merge() for combining datasets | 📙 Notebook
  • Pandas concat() tricks to speed up your data analysis | 📙 Notebook
  • 5 Tricks to master Pandas append() | 📙 Notebook
• Selecting and Querying
  • Pandas loc and iloc for selecting data | 📙 Notebook
  • Pandas Equivalents of various SQL queries | TBA soon
  • Creating conditional columns with Numpy select() and where() methods | 📙 Notebook
  • Accessing data in a MultiIndex DataFrame | 📙 Notebook
• Reshaping
  • Reshaping a DataFrame from wide to long format using melt() | 📙 Notebook
  • pivot() long to wide (work in progress)
  • stack() and unstack() (work in progress TBA)
• Grouping and Summarizing
  • Pandas groupby() for grouping data and performing operations | 📙 Notebook
  • A Practical Introduction to Pandas pivot_table() | 📙 Notebook
  • Summarizing data with Pandas crosstab() | 📙 Notebook
• Best Practice & Code Readability
  • Using Pandas pipe() to improve code readability | 📙 Notebook
  • Using Pandas method chaining to improve code readability | 📙 Notebook
  • 7 setups you should include at the beginning of a data science project | 📙 Notebook
  • 6 Pandas Tricks you should know to speed up your data analysis | 📙 Notebook
  • 8 Commonly used Pandas display options you should know | 📙 Notebook
• Introduction & Others
  • A Practical Introduction to Pandas Series | 📙 Notebook

Applied Data Analysis and EDA

• COVID-19 data processing with Pandas DataFrame | TBA soon

Web scraping

• Scraping tables from a JavaScript webpage using Selenium, BeautifulSoup, and Pandas | 📙 Notebook

Data Visualization

• Dual-axis combo chart in Python - Matplotlib, Seaborn, and Pandas plot() | 📙 Notebook
• Adding 3rd Y-axis to combo chart in Python - Matplotlib, Seaborn, and Pandas plot() | 📙 Notebook

Altair

• Python Interactive Data Visualization with Altair | Gist
• Interactive Data Visualization for exploring Coronavirus Spreads | Gist

Matplotlib

• Matplotlib animation in Jupyter Notebook | 📙 Notebook
• Matplotlib Linear Regression animation in Jupyter Notebook | 📙 Notebook

TensorFlow in practice

• The Google's 7 steps of Machine Learing in Practice | Notebook
• 3 ways to create a Machine Learning model with Keras and TensorFlow 2.0 | Notebook
• Model Regularization in practice | Notebook
• Batch Normalization in practice | Notebook
• Early Stopping in practice | Notebook
• Learning Rate schedules in Practice | Notebook
• Keras Callbacks in Practice | Notebook
• Keras Custom Callbacks | Notebook
• 7 popular activation functions in Deep Learning | Notebook
• Why ReLU in Deep Learning and the best practice | Notebook

Scikit-Learn in practice

• A Practical Introduction to Grid Search, Random Search, and Bayes Search | 📙 Notebook
• A Practical Introduction to 9 Regression Algorithms | 📙 Notebook
• Train-Test split and Cross-Validation you should know in Machine Learning (TBA) | 📙 Notebook

PyTorch in practice