Comprehensive Understanding to K-Nearest Neighbors (KNN) in Supervised Machine Learning. K-Nearest Neighbors (KNN) is a simple, widely used supervised learning algorithm in data science and machine learning It was developed by Evelyn Fix and Joseph Hodges in 1951. Known for it usefulness and versatality, KNN can handle both classification and regression tasks when needed. https://youtu.be/Nz73vXn5afE […]
Tree of Thought Prompting
In the ever-evolving field of artificial intelligence, reasoning and problem-solving capabilities have seen remarkable advancements. One such innovation that stands out is the use of Tree of Thoughts (TOT) in AI reasoning, particularly in the realms of mathematical reasoning and writing TOT excels in guiding the progression of thoughts, making the problem-solving process more comprehensive […]
Chain of Thought Prompting
Chain of Thought Prompting also known as COT is a way to enhance the reasoning and problem-solving abilities of Large Language Models (LLM). It helps guide the LLM through a step-by-step process to arrive at a final result. It’s like showing your work on a math problem. This is done by breaking down the prompt […]
Python Pandas GroupBy
Many data analysts begin their journey with SQL, learning how to use GROUP BY to aggregate and summarize data. As they advance, they often transition to Python for more complex data manipulation. One of the key features in Python’s Pandas library is the groupby function, which allows for powerful and flexible data grouping and aggregation. […]
Optuna Hyperparameter Tuning
Optuna is a hyperparameter optimization framework for machine learning models. It can help automate and streamline the process of tuning the hyperparameters. It’s quite popular among Kaggle users and you’ll see it used within competitions. In this article, we will go over an example of using it on a basic dataset. There is also a […]
Ordinal Encoder
When working with real world data, you’ll often have to deal with categorical information. This can be a problem when working with Machine Learning models as most cannot use it. Instead, Data Scientists and Machine Learning engineers need to convert this into a numerical format. This is where the Ordinal Encoder in Scikit-Learn can help. […]
One Hot Encoder
In the realm of machine learning and data science, preparing your data is often as crucial as the modeling itself. One of the essential preprocessing steps when working with categorical data is one-hot encoding. This technique transforms categorical variables into a format that can be provided to machine learning algorithms to improve predictions and insights. […]
Python Match Case Statement
The match case statement in Python introduces a powerful way to handle conditional logic, akin to the switch-case statements found in many other programming languages. By allowing you to match values against a variety of patterns and execute code based on the first pattern that is matched, the match case statement can make your code […]
Chat With a CSV Using LangChain
With just a few lines of code, you can use natural language to chat directly with a CSV file. In this tutorial, I’ll be taking you line by line to achieve results in less than 10 minutes. While still a bit buggy, this is a pretty cool feature to implement in a test tool. It’s […]
Langchain Agents
Welcome to our latest article on Langchain agents! In this guide, we’ll dive into the innovative approach to building agents introduced in Langchain update 0.1. By leveraging agents, you can significantly enhance the capabilities of the OpenAI API and seamlessly integrate external tools. Interested in discussing a Data or AI project? Feel free to reach […]