Cross Validation and EDA - Data Science Current

The Success Story of Microsoft’s Senior Data Scientist

Analytics Vidhya

JULY 8, 2023

Introduction In today’s digital era, the power of data is undeniable, and those who possess the skills to harness its potential are leading the charge in shaping the future of technology.

Data Scientist

Data Scientist Data Science Analytics Analytics

Sales Prediction| Using Time Series| End-to-End Understanding| Part -2

Towards AI

JULY 19, 2023

Please refer to Part 1– to understand what is Sales Prediction/Forecasting, the Basic concepts of Time series modeling, and EDA I’m working on Part 3 where I will be implementing Deep Learning and Part 4 where I will be implementing a supervised ML model. This is part 2, and you will learn how to do sales prediction using Time Series.

Cross Validation

Cross Validation Clustering EDA Data Preparation

The AI Process

Towards AI

AUGUST 16, 2023

Data preparation: This step includes the following tasks: data preprocessing, data cleaning, and exploratory data analysis (EDA). Training: This step includes building the model, which may include cross-validation.

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AI AI Machine Learning Machine Learning

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Announcing the Winners of ‘The NFL Fantasy Football’ Data Challenge

Ocean Protocol

SEPTEMBER 29, 2023

By leveraging cross-validation, we ensured the model’s assessment wasn’t reliant on a singular data split. Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create.

Cross Validation

Cross Validation Predictive Analytics Exploratory Data Analysis EDA

Feature Engineering in Machine Learning

Pickl AI

JANUARY 3, 2024

EDA, imputation, encoding, scaling, extraction, outlier handling, and cross-validation ensure robust models. Exploratory Data Analysis (EDA): A foundation for success The initial step in feature engineering is to conduct a meticulous Exploratory Data Analysis. Steps of Feature Engineering 1.

Machine Learning

Machine Learning Machine Learning Exploratory Data Analysis Cross Validation

The Easiest Way to Determine Which Scikit-Learn Model Is Perfect for Your Data

Mlearning.ai

NOVEMBER 23, 2023

You may need to import more libraries for EDA, preprocessing, and so on depending on the dataset you’re dealing with. But you might need to do deep EDA and some data preprocessing in this step for feature selection and to ensure your data fits well into the models. STEP 1: Install the lazypredict library.

Supervised Learning

Supervised Learning Cross Validation EDA Machine Learning

Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

JULY 12, 2024

Exploratory Data Analysis (EDA) EDA is a crucial preliminary step in understanding the characteristics of the dataset. EDA guides subsequent preprocessing steps and informs the selection of appropriate AI algorithms based on data insights. Feature Engineering : Creating or transforming new features to enhance model performance.

Artificial Intelligence

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Meet the winners of the Kelp Wanted challenge

DrivenData Labs

APRIL 10, 2024

Summary of approach: In the end I managed to create two submissions, both employing an ensemble of models trained across all 10-fold cross-validation (CV) splits, achieving a private leaderboard (LB) score of 0.7318.

Deep Learning

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New Data Challenge: Aviation Weather Forecasting Using METAR Data

Ocean Protocol

FEBRUARY 1, 2024

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). It’s also a good practice to perform cross-validation to assess the robustness of your model.

Exploratory Data Analysis

Exploratory Data Analysis Data Science Cross Validation Machine Learning

What is Regression Analysis?

Pickl AI

SEPTEMBER 18, 2024

Step 2: Exploratory Data Analysis (EDA): Before running Regression Analysis, it’s essential to perform EDA to visualise data distributions and identify any outliers or patterns that may influence results. This data can come from various sources such as surveys, experiments, or historical records.

EDA

EDA Exploratory Data Analysis Hypothesis Testing Cross Validation

AI in Time Series Forecasting

Pickl AI

DECEMBER 16, 2024

Exploratory Data Analysis (EDA): Conduct EDA to identify trends, seasonal patterns, and correlations within the dataset. Split the Data: Divide your dataset into training, validation, and testing subsets to ensure robust evaluation. Making Data Stationary: Many forecasting models assume stationarity.

AI

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

Mlearning.ai

MARCH 15, 2023

Data Extraction, Preprocessing & EDA & Machine Learning Model development Data collection : Automatically download the stock historical prices data in CSV format and save it to the AWS S3 bucket. Data Extraction, Preprocessing & EDA : Extract & Pre-process the data using Python and perform basic Exploratory Data Analysis.

Python

Python AWS Exploratory Data Analysis EDA

Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

SEPTEMBER 12, 2024

Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset. Exploratory Data Analysis (EDA): Analysing and visualising data to discover patterns, identify anomalies, and test hypotheses.

Data Analyst

Data Analyst Data Science Machine Learning Machine Learning

Large Language Models: A Complete Guide

Heartbeat

MAY 29, 2023

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. Use a representative and diverse validation dataset to ensure that the model is not overfitting to the training data.

Machine Learning

Machine Learning Machine Learning Natural Language Processing Data Preparation

Data Science Current

The Success Story of Microsoft’s Senior Data Scientist

Sales Prediction| Using Time Series| End-to-End Understanding| Part -2

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The AI Process

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Announcing the Winners of ‘The NFL Fantasy Football’ Data Challenge

Feature Engineering in Machine Learning

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Meet the winners of the Kelp Wanted challenge

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AI in Time Series Forecasting

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

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