Ahameddatailm.hashnode.dev·Sep 22, 2023Converting Categorical Variables for Machine Learning: One-Hot Encoding and Label Encoding TechniquesWhen dealing with categorical variables in your dataset, consider using one-hot encoding or label encoding to convert them into a numerical format that machine learning models can understand. You can apply one-hot encoding efficiently using libraries...DiscussData MiningData Preprocessing
Jude Nwabueze Echezonajaynwabueze.hashnode.dev·Aug 22, 2023Enhancing Machine Learning Models: A Guide to Feature Engineering for House Price PredictionIn the rapidly changing field of machine learning, where algorithms are always evolving, one fundamental reality stays constant: the importance of feature engineering. The art of translating raw data into an artwork of insights lies beyond the algori...DiscussMachine Learning
Tun Shwestereosky.hashnode.dev·Jul 13, 2023Real-Time Infrastructure for Data ScientistsIn our ongoing series on friction in feature engineering, we talked generally about the impedance gap between data scientists and engineers and did a deep dive into the hassle of translating Python into Java. Here, I want to do another deep dive, but...DiscussData Science
Om omdabralblogs.hashnode.dev·Jul 10, 2023Feature EngineeringBefore Beginning This Tutorial I would Like to show you the pictorial diagram of the complete Machine Learning Life Cycle As you can see there is a step called Data Preparation, this step is really important in the life cycle, it consists 3 substeps...Discuss·1 likeExploring The Basics Of Data Science: A Beginner's Guide
Yuvraj Singhyuvraj01.hashnode.dev·Jul 7, 2023Feature Scaling: A Guide for AI DevelopersI hope you are doing great, so today we will discuss an important topic in machine learning called feature scaling. After going through this blog you will be completely aware about which technique to use and when to use. So without any further dealy ...Discuss·10 likesWeMakeDevs
Vashon GonzalesforBankous Documentationbankous.paygeon.io·Jul 2, 2023Automated Underwriting Using Machine LearningAbstract: The Machine Learning Credit Card Underwriting Jupyter Notebook Module is a software tool designed to automate the process of credit card underwriting using machine learning algorithms. This module integrates various data sources, including ...DiscussUnderwritingMachine Learning
Tun Shwestereosky.hashnode.dev·Jun 28, 2023Feature Engineering Has a Language ProblemFeature engineering is a crucial part of any machine learning (ML) workflow because it enables more complex models to be created than with raw data alone, but it's also one of the most difficult to manage. It's afflicted by a language barrier—a diffe...Discussdata-engineering
Tanupriya Singhtanupriya.com·Apr 14, 2023Feature Engineering for BeginnersFeature Engineering is the process of preparing features (attributes/ characteristics) of the data, for your training model. Usually, the ETL (Extract, Transform, Load) step is expected to forward tidy data. But sometimes even the tidy data might nee...Discuss·38 readsfeature engineering
Rhythm Rawatrhythmblogs.hashnode.dev·Mar 28, 2023Everything you need to know about Feature EngineeringHey guys, hope you are doing great. In the previous article, we understood Exploratory Data Analysis. In this article, you'll know everything about feature engineering. Feature engineering is the process of creating new features from existing data th...Discuss·35 readsfeature engineering
Rhythm Rawatrhythmblogs.hashnode.dev·Mar 19, 2023Important concepts in Descriptive StatisticsHey everyone, hope you all are doing great. In this article, we will be covering some important concepts in Descriptive stats. Let's start Percentiles and quartiles Percentile is a comparison score between a particular score and all the scores in the...Discuss·2 likes·257 readsstatistics
