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, Time Series Analysis and Forecasting, Reinforcement Learning, Generative Model Architectures, Deep Learning, Data Analysis, Statistical Methods, Statistical Inference, Applied Machine Learning, Predictive Modeling, Statistical Hypothesis Testing, 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, Data Science, Applied Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Data Mining, Python Programming, Linear Algebra, NumPy, Algorithms, Exploratory Data Analysis

  • Status: Free Trial

    Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Algorithms, Keras (Neural Network Library), Unstructured Data, Probability & Statistics, Linear Algebra

  • Status: New
    Status: Free Trial

    Skills you'll gain: AI Personalization, Data Manipulation, Apache Spark, Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Natural Language Processing, AWS SageMaker, Scalability, Applied Machine Learning, Data Processing, Supervised Learning, Dimensionality Reduction, Machine Learning, Pandas (Python Package), Predictive Modeling, Python Programming, Time Series Analysis and Forecasting, Artificial Neural Networks

What brings you to Coursera today?

  • Status: New
    Status: Free Trial

    Skills you'll gain: Prompt Engineering, Generative AI, Dimensionality Reduction, Natural Language Processing, Large Language Modeling, OpenAI, Text Mining, Applied Machine Learning, LLM Application, Statistical Machine Learning, Data Processing, Databases, Feature Engineering, Python Programming, Supervised Learning, Artificial Intelligence, Unsupervised Learning, Pandas (Python Package), Data Transformation, NumPy

  • Status: Free Trial

    University of Minnesota

    Skills you'll gain: AI Personalization, Machine Learning Algorithms, Taxonomy, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Performance Measurement, Benchmarking, Usability Testing, Exploratory Data Analysis, A/B Testing, Analysis, User Feedback, Algorithms, System Design and Implementation, Solution Design, Data-Driven Decision-Making, Predictive Modeling

  • Status: New
    Status: Free Trial

    Skills you'll gain: Sampling (Statistics), Matplotlib, Data Analysis, Data Mining, Statistical Analysis, Statistical Hypothesis Testing, NumPy, Pandas (Python Package), Probability Distribution, Dimensionality Reduction, R Programming, Probability, Python Programming, Scikit Learn (Machine Learning Library), Linear Algebra, Applied Machine Learning, Unsupervised Learning, Regression Analysis, Statistical Methods, Artificial Intelligence and Machine Learning (AI/ML)

  • Status: New
    Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Seaborn, Matplotlib, Predictive Modeling, Supervised Learning, NumPy, Applied Machine Learning, Predictive Analytics, Dimensionality Reduction, Random Forest Algorithm, PyTorch (Machine Learning Library), Deep Learning, Keras (Neural Network Library), Scatter Plots, Tensorflow, Statistical Visualization, Python Programming, Data Science, Machine Learning, Data Analysis

  • Status: Free Trial

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Jupyter

  • 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, Machine Learning, Predictive Modeling, Python Programming, Classification And Regression Tree (CART), Data Science, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling

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