- 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
- Using Pandas pipe function to improve code readability | 📙 Notebook
- Using Pandas method chaining to improve code readability | 📙 Notebook
- What is One-Hot Encoding and how to use Pandas get_dummies function | 📙 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
- 4 tricks you should know to parse date columns with Pandas
read_csv()| 📙 Notebook - Pandas
read_csv()tricks you should know | 📙 Notebook - Working with datetime in Pandas DataFrame | 📙 Notebook
- When to use Pandas
transform()function | 📙 Notebook - Difference between
apply()andtransform()in Pandas | 📙 Notebook - Introduction to Pandas
apply(),applymap(), andmap()| TBA soon - Working with missing values in Pandas | TBA soon
- Pandas Equivalents of various SQL queries | TBA soon
- A Practical Introduction to Pandas
pivot_table()| 📙 Notebook - Creating conditional columns on Pandas with Numpy
select()andwhere()methods | 📙 Notebook - How to do a Custom Sort on Pandas DataFrame | 📙 Notebook
- Pandas
concat()tricks you should know to speed up your data analysis | 📙 Notebook - Pandas
resample()tricks you should know for manipulating time-series data | 📙 Notebook - All the Pandas
merge()you should know for combining datasets | 📙 Notebook - All the Pandas
shift()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
- A Practical Introduction to Pandas Series | 📙 Notebook
- Pandas
cut()to transform numerical data into categorical data | 📙 Notebook - Pandas
qcut()for binning numerical data based on sample quantiles | 📙 Notebook - Pandas
json_normalize()for flattening JSON | 📙 Notebook - Renaming columns in a Pandas DataFrame | 📙 Notebook
- Pandas
groupby()for grouping data and performing operations | 📙 Notebook - Pandas
locandilocfor selecting data | 📙 Notebook - Accessing data in a MultiIndex DataFrame | 📙 Notebook
- Finding and removing duplicate rows in Pandas DataFrame | 📙 Notebook
- 10 tricks for Converting data to a numeric type in Pandas | 📙 Notebook
- 10 tricks for Converting numbers and strings to datetime in Pandas | 📙 Notebook
- 8 Commonly used Pandas display options you should know | 📙 Notebook
- 9 Pandas
value_counts()tricks | 📙 Notebook - Getting more value from the Pandas
count()| 📙 Notebook - 11 Tricks to Master
sort_values()in Pandas | 📙 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
- 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
- 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