Category: Weekly Article News

The recommended articles the author has read this week.

Python open source libraries for scaling time series forecasting solutions

This article, written by the engineer at Microsoft, is so informative because many open source libraries are introduced for time series forecasting, including from low-level library(e.g. NumPy, SciPy) to high-level library(e.g. scikit-learn, Prophet, PyFlux, Sktime).

PyCaret 2.3.5 Is Here! Learn What’s New

Notification version release of PyCaret.
In version 2.3.5, some minor updates have been performed. For example, a dummy model for regression and classification is added. Besides, we are now able to change the probability threshold, default is 0.5, for such as logistic regression. And also, we can use an ipywigets dashboard from this version.

The recommended articles the author has read this week.

Bye-bye PowerPoint. Hello Marp!

We spend a lot of time creating slides of PowerPoint. This article introduces a new tool for creating slides, which can replace PowerPoint. The new tool is available with Visual Studio code and Markdown style.

4 Amazing Python Libraries That You Should Try Right Now

This article introduces several useful python libraries, especially for a data scientist. For example, one of them is “opendatasets“, a library for easy importing kaggle open datasets.

The recommended articles the author has read this week.

How to Find the Second Largest Element in a List in Python

The author felt a topic is interesting. For a programmer, algorithms are important. In practice, flexible thinking is important. And leave the idea as a comment.

Feature Engineering for Time Series problem

Time series analysis is a little bit different from other analyses. In particular, the way of verification and feature engineering is unusual, so this is an area that you should know at least once.

The recommended articles the author has read this week.

How To use Google Colab with VS Code

Google colab is useful because we can use GPU for free! However, we could NOT use the colab from VS code, a modern editor for code editing. This article tells us how to use colab from VS code.

Python Decorators: Everything You Need to Know

Python decorator is a useful function, whereas it is unfamiliar to a beginner. This article explains decorators with brief descriptions.

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

Detecting Car Damage Using Deep Learning

A good example to learn object detection by Tensorflow. In this article, the code and its description are easy to understand.

Anomaly Detection Using PyCaret!!!

Pycaret is an open-source low-code machine learning library in Python. By Pycaret, we can easily deploy a machine learning model. In this article, we can know it is also easy to perform an anomaly-detection analysis by Pycaret!

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

An Introduction to Regular Expressions in Python

Regular expressions are one of the most essential skills, increasing your productivity. This article introduces how to use the “re” module, a famous build-in python library for regular expressions. It would be worth reading if you are unfamiliar with regular expressions.

Machine Learning for ESG Stock Trading: PCA and Clusterin

This article is a long story, but informative. We can learn an example to use machine learning for finance. The topic is pair trading. We use machine learning to select the pair for long and short positions.

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

3 Low-Code Machine Learning Libraries that You Should Know About

This article introduces the three famous low-code python libraries for Machine learing, i.e., PyCaret, TPOT, and LazyPredict. It would be worth to read if you are interested in a low-code library for Machine learning.

Do Not Use Print For Debugging In Python Anymore

The “IceCream”, a python library, is practical for debugging your codes. In this article, the usage is introduced in a concrete example.

An Intuitive Explanation of Random Forest and Extra Trees Classifiers

The article explains the difference between random forest and extra trees classifiers, where both methods are implemented in scikit-learn.

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

Lasso (l1) and Ridge (l2) Regularization Techniques

A brief description of Lasso and Ridge regularization techniques. From this article, we can learn the difference between them.

Improve Your Python Code With These Useful Features

This article introduces several useful python techniques. Especially, I was impressed by decorators. The example is practical.

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

Creating the Perfect Python Dockerfile

This article tells us some good points to consider when creating a Dockerfile for building a Python environment.

Mastering Streamlit: Multi-Paged Stock Tracker Dashboard

It’s an impression for intermediate users, but this article tells us useful information.

[News] A streamlit tutorial book has been published on Amazon Kindle!

I have published the book for a tutorial of Streamlit; “Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist”.

This new book is registered on Kindle Unlimited, so any member can read it !!

Features of this book

• For beginners of Streamlit
• Be aware of simple explanations
• All with sample code
• Introducing data analysis as a web application as an example

The recommended articles the author has read this week.

How to Work with Excel files in Pandas

Most of data scientists may use CSV files instead of Excel format files(.xls or .xlsx). A CSV file is useful because of its simple format or rule(comma separated). However, you may encounter the situation that you want to use an Excel format file. This article tells how to treat an Excel format file step-by-step.

Predict Customer Churn (the right way) using PyCaret

An example of data analyses in business fields using PyCaret. PyCaret is a low-code machine learning library, making it possible to build machine-learning models faster and compare them. Besides, in this article, there is a description of how to add custom a metric in PyCaret.