Machine Learning
Practical Machine Learning topics for articles in my Medium blog
Content
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
- Data Profiling
- Data Preprocessing
- What is One-Hot Encoding and how to use
get_dummies()| - Working with missing values in Pandas | TBA soon
- Working with datetime in Pandas DataFrame |
- 11 Tricks to Master
sort_values()in Pandas | - How to do a Custom Sort on Pandas DataFrame |
- Pandas
cut()to transform numerical data into categorical data | - Pandas
qcut()for binning numerical data based on sample quantiles | - Finding and removing duplicate rows in Pandas DataFrame |
- Renaming columns in a Pandas DataFrame |
- 10 tricks for Converting data to a numeric type |
- 10 tricks for Converting numbers and strings to datetime |
- Pandas
resample()tricks for manipulating time-series data | - When to use Pandas
transform()function | - Difference between
apply()andtransform()in Pandas | - Introduction to Pandas
apply(),applymap(), andmap()| TBA soon - All the Pandas
shift()you should know | - Delete rows/columns from a DataFrame using
drop()| - Flatten MultiIndex columns and rows |
- What is One-Hot Encoding and how to use
- Combining data
- Selecting and Querying
- Reshaping
- Grouping and Summarizing
- Best Practice & Code Readability
- Using Pandas
pipe()to improve code readability | - Using Pandas method chaining to improve code readability |
- 7 setups you should include at the beginning of a data science project |
- 6 Pandas Tricks you should know to speed up your data analysis |
- 8 Commonly used Pandas display options you should know |
- Using Pandas
- Introduction & Others
Applied Data Analysis and EDA
Web scraping
Data Visualization
- Dual-axis combo chart in Python - Matplotlib, Seaborn, and Pandas
plot()| - Adding 3rd Y-axis to combo chart in Python - Matplotlib, Seaborn, and Pandas
plot()|
Altair
- Python Interactive Data Visualization with Altair | Gist
- Interactive Data Visualization for exploring Coronavirus Spreads | Gist
Matplotlib
- Matplotlib animation in Jupyter Notebook |
- Matplotlib Linear Regression animation in Jupyter Notebook |
TensorFlow
- The Google's 7 steps of Machine Learing in Practice |
- 3 ways to create a Machine Learning model with Keras and TensorFlow 2.0 |
- Model Regularization in practice |
- Batch Normalization in practice |
- Early Stopping in practice |
- Learning Rate schedules in Practice |
- Keras Callbacks in Practice |
- Keras Custom Callbacks |
- 7 popular activation functions in Deep Learning |
- Why ReLU in Deep Learning and the best practice |
PyTorch
TBA
Scikit-Learn and General Machine Learning
- A Practical Introduction to Grid Search, Random Search, and Bayes Search |
- A Practical Introduction to 9 Regression Algorithms |
- Train-Test split and Cross-Validation you should know in Machine Learning (TBA) |