Remove Cross Validation Remove Exploratory Data Analysis Remove ML Remove Python
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New Data Challenge: Aviation Weather Forecasting Using METAR Data

Ocean Protocol

Challenge Overview Objective : Building upon the insights gained from Exploratory Data Analysis (EDA), participants in this data science competition will venture into hands-on, real-world artificial intelligence (AI) & machine learning (ML). You can download the dataset directly through Desights.

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Unlocking the Power of KNN Algorithm in Machine Learning

Pickl AI

Experimentation and cross-validation help determine the dataset’s optimal ‘K’ value. Distance Metrics Distance metrics measure the similarity between data points in a dataset. Implementing the KNN algorithm involves several steps, from preprocessing the data to training the model and making predictions.

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development.

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

Mlearning.ai

After doing all these cleaning steps data looks something like this: Features after cleaning the dataset Exploratory Data Analysis Through the data analysis we are trying to gain a deeper understanding of the values, identify patterns and trends, and visualize the distribution of the information.

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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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Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit?—?Part 2 of 3

Mlearning.ai

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. Introduction Welcome Back, Let's continue with our Data Science journey to create the Stock Price Prediction web application.

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Large Language Models: A Complete Guide

Heartbeat

It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text. The ML process is cyclical — find a workflow that matches. The ML process is cyclical — find a workflow that matches.