#144 - Install Python and VSCode in a Windows PC without admin rights

1. From SW Center install Microsoft Visual Studio Code and install the extension Python (shortcut is CTRL + SHIFT + X)

2. From Python download the latest available release of the "Windows embeddable package (64-bit)", currently v3.11.0

#103 - Time-series classification of power demand comparison between Sktime and Sklearn

Using the public dataset that represents the power consumption in Italy in 1997, the task is to classify whether it corresponds to winter (from October to March) or summer (from April to September). This will be done using different techniques from both sklearn and sktime. 

#102 - Public time-series datasets

The following website http://timeseriesclassification.com/ has a great amount of public time-series datasets for several applications such as data from sensors, motion, image, audio, among others. In this post is shown how to use these datasets in a python framework.

#101 - Time-series forecast with sktime and python

Several applications in production, from finance to industrial systems, have the data being recorded and indexed by timestamps. In this post we are presenting a great open source library for python called sktime, which  was recently launched and has been developed and optimized for machine learning time-series classification, regression and forecasting. 

#100 - Switching between Python versions

Sometimes it may be required to switch between Python versions. For example, if some library does not have support yet for the current installed Python version. One way to overcome this is by checking the stable version required for that library then downloading and installing it from the python website.

#87 - Machine Learning classification comparison between GridSearchCV and RandomizedSearchCV

In a dataset with 13 features that represent different wine properties, such as color intensity and alcohol content, a machine learning model is created for a classification task. The goal is to predict in which class these wines belong, that could be class 0, class 1 or class 2. 

#85 - Using Pandas to transform categorical data for machine learning models

When creating machine learning models in python, using for instance the libraries numpy, pandas and sklearn, depending on the algorithms selected, the input data should be on the numerical format.

#80 - Another resource for practicing Data Science interview questions

On the previous post, it was showed one website with great content to develop your skills in Data Science by practicing in interview questions.

#79 - Using Python's pdb debugger

Python has a library called pdb that can be imported into the project and it is very straight-forward to use. 

#73 - Data Science interview questions

This website offers a great way to keep continuously practicing on key topics related to data science, such as Python, statistics and SQL. The user can subscribe to their mailing list and receive for free 3 interview questions per week. There's also a paid version with additional benefits. 

#68 - Key points about Pandas (Python library)

Pandas is one of the key libraries used in Python for data manipulation and data analysis. It runs on the top NumPy, which is another important Python library.