Dimensionality Reduction

Dimensionality Reduction is a data preprocessing technique used in machine learning, which reduces the number of random variables to consider by obtaining a set of principal variables. Coursera's Dimensionality Reduction catalogue teaches you to handle high-dimensional data, enhance computational efficiency, and prevent overfitting. You'll learn to implement methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Non-negative Matrix Factorization (NMF). You'll also understand how to visualize high-dimensional datasets, improve model performance, and handle issues related to underfitting and overfitting. This knowledge will empower you to tackle complex machine learning problems, data analysis tasks, and make sense of large datasets.
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Results for "dimensionality reduction"

  • Status: Free Trial

    Imperial College London

    Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Machine Learning Algorithms, Jupyter, Data Science, Advanced Mathematics, Statistics, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming, Machine Learning, Derivatives

  • Status: Free Trial

    Skills you'll gain: Dimensionality Reduction, NumPy, Probability & Statistics, Jupyter, Data Science, Statistics, Linear Algebra, Python Programming, Machine Learning, Calculus

  • Status: Free Trial

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Generative Model Architectures, Deep Learning, Data Analysis, Statistical Methods, Applied Machine Learning, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Processing, Machine Learning Algorithms, Machine Learning, Data Science, Python Programming

  • Status: Free Trial

    University of Colorado Boulder

    Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Machine Learning Algorithms, Machine Learning, Data Science, Scikit Learn (Machine Learning Library), Python Programming, NumPy, Exploratory Data Analysis, Linear Algebra, Statistical Analysis

  • Status: New
    Status: Preview

    Skills you'll gain: Mathematical Modeling, Linear Algebra, Dimensionality Reduction, Applied Mathematics, Data Analysis, Applied Machine Learning, Analytics, Data Science

  • Status: New
    Status: Free Trial

    Skills you'll gain: Rmarkdown, Version Control, Web Scraping, Regression Analysis, Knitr, Exploratory Data Analysis, Statistical Analysis, Data Manipulation, Dimensionality Reduction, Ggplot2, Geospatial Information and Technology, Time Series Analysis and Forecasting, Plotly, Shiny (R Package), Data Cleansing, Data Visualization, Data Wrangling, Software Documentation, R Programming, Microsoft Copilot

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  • Status: Free Trial

    University of Colorado Boulder

    Skills you'll gain: Unsupervised Learning, Regression Analysis, Dimensionality Reduction, Data Analysis, Anomaly Detection, Supervised Learning, Machine Learning, Analytics, Predictive Modeling, Statistical Analysis, Applied Machine Learning, Statistical Modeling, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Data Mining, Machine Learning Algorithms, Exploratory Data Analysis, Machine Learning Methods, Feature Engineering, Data Science

  • Status: Free Trial

    Skills you'll gain: Data Wrangling, Linear Algebra, Regression Analysis, Data Manipulation, NumPy, Predictive Modeling, Dimensionality Reduction, Data Science, Applied Mathematics, Statistical Modeling, Mathematical Software, Supervised Learning, Algebra, Data Visualization Software, Jupyter, Data Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Numerical Analysis, Python Programming

  • Status: New
    Status: Free Trial

    Birla Institute of Technology & Science, Pilani

    Skills you'll gain: Linear Algebra, Artificial Intelligence and Machine Learning (AI/ML), Applied Mathematics, Numerical Analysis, Machine Learning, Artificial Neural Networks, Dimensionality Reduction, Data Analysis

  • Status: Preview

    University of Minnesota

    Skills you'll gain: Dimensionality Reduction, NumPy, Linear Algebra, Machine Learning Methods, Data Analysis, Numerical Analysis, Applied Mathematics, Applied Machine Learning, Algorithms, Python Programming

  • Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Deep Learning, Machine Learning Algorithms, Dimensionality Reduction, Applied Machine Learning, Decision Tree Learning, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Predictive Modeling, Python Programming, Classification And Regression Tree (CART), Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Machine Learning, Data Science

  • Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Feature Engineering, Applied Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning, Predictive Modeling, Dimensionality Reduction, Regression Analysis, Decision Tree Learning, Classification And Regression Tree (CART), Statistical Modeling

What brings you to Coursera today?

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