Statistical Machine Learning

Statistical Machine Learning is a subset of artificial intelligence that leverages statistical techniques to enable machines to improve at tasks. Coursera's Statistical Machine Learning catalogue equips you with the ability to develop and apply predictive algorithms based on statistical concepts. You'll learn to build models, interpret results, and make predictions using machine learning techniques. Further, you'll gain an understanding of various statistical learning methods such as regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. This skill set can be used in various fields like data science, finance and banking, healthcare, retail, and more where predictive analysis is crucial.

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Results for "Statistical Machine Learning"

  • Google

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    4.8 stars, 647 reviews, Advanced, Course, 1 - 3 Months

  • EDUCBA

    Skills you'll gain: Matplotlib, Feature Engineering, Data Preprocessing, NumPy, Plot (Graphics), Tensorflow, Pandas (Python Package), Data Visualization, Model Training, Statistical Visualization, Data Wrangling, Jupyter, Applied Machine Learning, Seaborn, Statistical Machine Learning, Data Engineering, Machine Learning, Development Environment, Network Model, Network Engineering

    Beginner · Specialization · 1 - 3 Months

  • Board Infinity

    Skills you'll gain: Anomaly Detection, Feature Engineering, Fraud detection, Unsupervised Learning, Continuous Monitoring, Autoencoders, MLOps (Machine Learning Operations), Machine Learning Methods, Statistical Machine Learning, Model Training, Time Series Analysis and Forecasting, System Monitoring, Applied Machine Learning, Model Deployment, Statistical Analysis, Taxonomy

    Beginner · Course · 1 - 4 Weeks

  • IBM

    Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning Methods, Model Training, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Model Evaluation, Data Preprocessing, Feature Engineering, Model Optimization, Statistical Analysis, Statistical Methods, Classification Algorithms

    4.7 stars, 848 reviews, Intermediate, Course, 1 - 3 Months

  • IBM

    Skills you'll gain: Classification Algorithms, Supervised Learning, Model Evaluation, Data Preprocessing, Logistic Regression, Machine Learning Algorithms, Decision Tree Learning, Applied Machine Learning, Model Training, Statistical Machine Learning, Predictive Modeling, Business Logic, Machine Learning Methods, Scikit Learn (Machine Learning Library), Data Cleansing, Machine Learning, Regression Analysis, Random Forest Algorithm, Model Optimization, Sampling (Statistics)

    4.8 stars, 470 reviews, Intermediate, Course, 1 - 3 Months

  • Packt

    Skills you'll gain: Supervised Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Model Deployment, Machine Learning Methods, Classification And Regression Tree (CART), Model Evaluation, Machine Learning, Machine Learning Software, Statistical Machine Learning, Classification Algorithms, Machine Learning Algorithms, Model Training, Model Optimization, Predictive Modeling, Decision Tree Learning, Python Programming, Bayesian Statistics, Data Science, Web Services

    Intermediate · Course · 1 - 3 Months

  • DeepLearning.AI

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Probability, Statistical Inference, Statistics, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Correlation Analysis, Histogram, Statistical Visualization, Box Plots

    4.6 stars, 701 reviews, Intermediate, Course, 1 - 4 Weeks

  • University of Pennsylvania

    Skills you'll gain: Statistical Machine Learning, Model Evaluation, Statistical Methods, Logistic Regression, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning Methods, Machine Learning, Classification Algorithms, Regression Analysis, Statistical Analysis, Applied Machine Learning, Predictive Modeling, Probability & Statistics, Bayesian Statistics, Dimensionality Reduction, Statistical Hypothesis Testing, Model Optimization

    5 stars, 6 reviews, Intermediate, Course, 1 - 4 Weeks

  • Coursera

    Skills you'll gain: Supervised Learning, Model Optimization, Model Training, Applied Machine Learning, Statistical Machine Learning, Classification And Regression Tree (CART), Machine Learning Methods, Decision Tree Learning, Predictive Modeling, Machine Learning, Fine-tuning, Machine Learning Algorithms, Model Evaluation, Logistic Regression, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Random Forest Algorithm, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • EDHEC Business School

    Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Portfolio Risk, Applied Machine Learning, Asset Management, Network Analysis, Investments, Data Visualization Software, Machine Learning Methods, Return On Investment, Statistical Machine Learning, Financial Statement Analysis, Financial Data, Market Data, Financial Management, Unstructured Data, Predictive Modeling, Web Scraping, Risk Management

    4.6 stars, 1.8K reviews, Beginner, Specialization, 3 - 6 Months

  • EDUCBA

    Skills you'll gain: Tensorflow, Feature Engineering, Model Training, Data Preprocessing, Model Optimization, Image Analysis, Logistic Regression, Computer Vision, Applied Machine Learning, Data Processing, Model Evaluation, Machine Learning Methods, Artificial Neural Networks, Data Transformation, Machine Learning Software, Deep Learning, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Network Model

    Mixed · Course · 1 - 4 Weeks

  • Coursera

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Forecasting, Data Processing, Anomaly Detection

    4.3 stars, 20 reviews, Intermediate, Course, 1 - 4 Weeks