The Transformative Role of Large Language Models in Time Series Forecasting
Time Series Forecasting (TSF) is crucial in data science for predicting future values from historical data. Traditional methods often struggle with complex, variable data, but Large Language Models (LLMs) offer new capabilities. LLMs excel in capturing intricate patterns and handling unstructured data like text, enhancing forecast accuracy. They are...
From Hypothesis to Insights: A Step-by-Step Guide for people interested in Machine Learning Engineering
In this article I describe a series of steps that I learned through study and practise, each crucial for the success of ADSAI project. The steps are based on best […]...
Setting Up a Python Streamlit Environment on a Synology NAS
In this post, I will walk you through the process of setting up an environment for running Python Streamlit scripts on a Synology NAS as part of my experiences with […]...
Raspberry Pi controlled kiln (part 2)
In my previous post on making a raspberry pi controlled kiln I reached the point with a script running on my Raspberry PI to measure the temperature and manually switch […]...
Raspberry Pi controlled ceramic kiln
In this series of articles I am sharing my experiences with building a Raspberry Pi-controlled kiln from a second hand kiln. In this initial installment, I share my process of […]...
Merging dataframes with Pandas
Performing Anti-Joins Merge employees and top_cust with a left join, setting indicatorargument to True. Save the result to empl_cust. Select the srid column of empl_cust and the rows where _merge is 'left_only'. Save the result to srid_list. Subset the employees table and select those rows where the srid is […]...
Object Oriented Programming in Python
In normal life to tend to think in sequences of activities. Procedural programming Code as a sequence of steps Great for data analysis and scripts Object-oriented programming Code as interactions […]...
How to create a DataFrame in Pandas from a list and add columns
Imagine we have a list and we want to be able to use it as a Pandas DataFrame in Python, how do we do that? And just for fun, I […]...
Reading a .csv file with Python and creating a DataFrame
In this chapter I will dive into reading the data in .csv file and creating a DataFrame. A .csv file stands for comma-separated value, so it simply contains a set […]...