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Data Science Project?—?Build a Decision Tree Model with Healthcare Data

Mlearning.ai

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

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Data Science Project?—?Predictive Modeling on Biological Data

Mlearning.ai

Data Science Project — Predictive Modeling on Biological Data Part III — A step-by-step guide on how to design a ML modeling pipeline with scikit-learn Functions. Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. Now comes the exciting part ….

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Decoding METAR Data: Insights from the Ocean Protocol Data Challenge

Ocean Protocol

METAR, Miami International Airport (KMIA) on March 9, 2024, at 15:00 UTC In the recently concluded data challenge hosted on Desights.ai , participants used exploratory data analysis (EDA) and advanced artificial intelligence (AI) techniques to enhance aviation weather forecasting accuracy.

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Feature Engineering in Machine Learning

Pickl AI

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. Through Exploratory Data Analysis , imputation, and outlier handling, robust models are crafted. Time features Objective: Extracting valuable information from time-related data.

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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation.

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Top 10 Data Science Interviews Questions and Expert Answers

Pickl AI

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity. I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments.