Haocheng Linhaochengcodedev.hashnode.dev·Apr 28, 2024Understanding Data TypesIntroduction 📂 In the realm of academia, data is king. Whether conducting research 🔬, analyzing experiments 🧪, or exploring datasets 🔢, understanding the nuances of different data types is essential for accurate analysis and interpretation. 📚 I...DiscussData Science
Md Shahriyar Al Mustakim Mitulmitul-shahriyar.hashnode.dev·Apr 23, 2024Machine Learning : Data Pre Processing Part 1In this blog, we are using the data set called 'Data.csv' CountryAgeSalaryPurchased France4472000No Spain2748000Yes Germany3054000No Spain3861000No Germany40Yes France3558000Yes Spain52000No France4879000Yes Germany5083000No France376...Discuss·1 like·85 readsMachine Learning
Saurabh Naiksaurabhz.hashnode.dev·Apr 12, 2024Data Preprocessing Innovations: Document Image Analysis and Table Extraction for GenAIIntroduction: In the landscape of AI-driven applications like GenAI, effective data preprocessing is pivotal for extracting valuable insights from raw documents. Document Image Analysis and Table Extraction serve as foundational techniques, enabling ...DiscussGenerative AIData Science
Saurabh Naiksaurabhz.hashnode.dev·Apr 12, 2024Maximizing GEN-AI Performance: A Guide to Data Preprocessing TermsIntroduction: In the realm of AI-driven solutions, the quality of data preprocessing plays a crucial role in determining the effectiveness and efficiency of models. However, data preprocessing for GENAI, with its diverse range of document types and e...DiscussGenerative AIhybrid search
TJ GokcenProtjgokcen.com·Apr 12, 2024Part 3: Optimizing Machine Learning WorkflowsThe optimization of Machine Learning Workflows begins with the segregation of data into training, validation, and testing sets. However, before we do anything with our data, we need to "clean" it up. The broader term that is used in Machine Learning ...DiscussAn Introduction to Data Training: Laying the Foundation for Machine LearningModel Optimization
Binal Weerasenabinalweerasena.hashnode.dev·Mar 7, 2024Strategies for Handling Missing ValuesIn the domain of Data Mining, it is quite important to handle the missing values and outliers in a dataset since it would immensely affect the data analysis and the business decisions if not properly taken care of. Although it seems negligible for be...DiscussData Science
Pius Mutumamutuma.hashnode.dev·Dec 2, 2023Scaling data in Machine Learning. When is it important?When seeking to build a machine learning model, data is the food you add to a cooking pot, and Scaling is the final spice and salt that completes the meal: the model. Introduction Data comes in various formats, representing different variables. In th...DiscussFeature scaling
Saurabh Naiksaurabhz.hashnode.dev·Nov 29, 2023Mastering Text Preprocessing for NLP Tasks: A Comprehensive GuideIntroduction Text preprocessing is a critical step in Natural Language Processing (NLP) that involves transforming raw text data into a format suitable for analysis and machine learning models. It plays a crucial role in enhancing the quality of data...DiscussNatural Language processingArtificial Intelligence
Saurabh Naiksaurabhz.hashnode.dev·Nov 10, 2023Handling Missing Data: A Comprehensive Guide for Data ScientistsIntroduction: As data scientists, the responsibility of handling missing values is paramount before unleashing the power of machine learning algorithms. In this comprehensive guide, we'll explore the intricacies of dealing with missing data, comparin...DiscussData Science project lifecycleArtificial Intelligence
Eugene Dentehcodeaday.hashnode.dev·Oct 16, 2023Scaling SuccessIn the realm of machine learning, success often hinges on the details, and one of the fundamental yet frequently overlooked details is feature scaling. Picture this: you're embarking on a journey to explore the fascinating world of machine learning, ...DiscussNormalization and Standardization
