proximusembedded08.hashnode.dev·Apr 4, 2024Column Transformation in Machine LearningDiscover the key techniques and strategies for effective column transformation in machine learning. Understanding Column Transformation Column transformation is a technique used in machine learning to preprocess data before feeding it into a model. I...DiscussMachine Learning
LAKSHMI PRABHA Slakshmiprabha.hashnode.dev·Mar 28, 2024Feature Engineering Explained for Curious Minds😎Introduction: Imagine you have a big box of LEGO bricks 🧱. Each brick is like a piece of information about something. Maybe it's how tall someone is, or how fast a car 🚓can go. Now, just having lots of LEGO bricks doesn't really make anything excit...Discuss·3 likesfeature construct
TJ GokcenProtjgokcen.com·Feb 21, 2024Part 2: Data Collection and Preparation for Machine LearningIntroduction: The Foundation of Machine Learning The journey towards creating a robust machine learning model begins long before the first line of code is written—it starts with data. That's right, data is the real hero of our story. The collection a...DiscussAn Introduction to Data Training: Laying the Foundation for Machine LearningMachine Learning
Konrad RyłkoProagileandcode.com·Feb 19, 2024Optimize ML with Feature EngineeringIn this article, I'll focus on getting as much value as possible from training data, particularly features. We'll continue our journey started in Linear Regression model using Elixir and Nx. Let's jump into the practice and learn how to squeeze lemon...Discuss·1 likeMachine Learning in ElixirMachine Learning
proximusembedded08.hashnode.dev·Jan 28, 2024Feature engineering in MLIn this blog 🗒️ I will write about Feature engineering in machine learning and why it's important in terms of machine learning and also why we do feature engineering before training a ML model. If you are learning 🧑💻 machine learning so you alrea...DiscussMachine Learning
Jeremiah Katumojeremykatumo.hashnode.dev·Jan 16, 2024Essential data cleaning steps for machine learning algorithmsDATA CLEANING IN PYTHON AND R Data cleaning is the most crucial part in preparing data for machine learning algorithms. Data cleaning involves various steps to be conducted in order to work with a more consistent dataset. We are aware that most machi...DiscussMachine Learning
Derek Onwudiwetecheffect.hashnode.dev·Nov 20, 2023Feature Engineering: MLFeature engineering is crucial in machine learning as it involves transforming raw data into a format that enhances model performance. Well-crafted features can significantly impact a model's ability to understand patterns and make accurate predictio...DiscussMachine Learning
Saurabh Naiksaurabhz.hashnode.dev·Nov 13, 2023Mastering Feature Engineering: Elevate Your Machine Learning Dataset with Precision and PowerIntroduction: Embarking on the journey of building robust machine learning models is a thrilling endeavor, and at the heart of this pursuit lies the critical art of feature engineering. The process of transforming raw data into meaningful, predictive...DiscussData Science project lifecycleData Science
Saurabh Naiksaurabhz.hashnode.dev·Nov 13, 2023Mastering Imbalanced Datasets in Machine Learning: Techniques and Python ImplementationIntroduction: In the realm of machine learning, datasets are often imbalanced, where one class significantly outnumbers the others. This imbalance can pose challenges, affecting the performance and accuracy of models, especially for classification ta...DiscussData Science project lifecycleMachine Learning
Saurabh Naiksaurabhz.hashnode.dev·Nov 9, 2023Harmonizing Data Diversity: Strategies for Mixed Data and Date-Time FeaturesIntroduction: As we venture into the world of data, the amalgamation of categorical and numerical values within a feature, known as mixed data, presents a unique set of challenges. This blog explores the intricacies of handling mixed data and delves ...DiscussData Science project lifecycleMachine Learning