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  • Bayesian Methods For Machine Learning

Results for "bayesian methods for machine learning"


  • G

    Google Cloud

    Machine Learning on Google Cloud

    Skills you'll gain: Feature Engineering, Generative AI, Model Deployment, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Machine Learning, Data Preprocessing, MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Data Cleansing, Data Quality, AI Enablement, Prompt Engineering, Cloud Deployment, Supervised Learning, Scikit Learn (Machine Learning Library), AI Workflows, Cloud Computing

    4.4
    Rating, 4.4 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Specialization · 3 - 6 Months

  • M

    Microsoft

    Data Analytics and Machine Learning for Big Data

    Skills you'll gain: Apache Spark, MLOps (Machine Learning Operations), Large Language Modeling, Keras (Neural Network Library)

    Intermediate · Course · 1 - 3 Months

  • C

    Coursera

    Probabilistic Graphical Models: A Compact Introduction

    Skills you'll gain: Bayesian Network, Predictive Modeling, Machine Learning Methods, Markov Model, Statistical Modeling, Artificial Intelligence, Statistical Inference, Graph Theory, Network Analysis, Probability & Statistics, Sampling (Statistics), Algorithms, Scalability

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Machine Learning with R

    Skills you'll gain: Model Evaluation, Classification Algorithms, R Programming, Apache Spark, Deep Learning, Applied Machine Learning, Keras (Neural Network Library), Unsupervised Learning, Apache Hadoop, Data Preprocessing, Data Science, Machine Learning, Tensorflow, Data Mining, Tidyverse (R Package), Regression Analysis, Data Analysis, Bayesian Network, Logistic Regression

    Intermediate · Course · 3 - 6 Months

  • D

    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    679 reviews

    Intermediate · Course · 1 - 4 Weeks

  • D

    Duke University

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Probability Distribution

    3.8
    Rating, 3.8 out of 5 stars
    ·
    798 reviews

    Intermediate · Course · 1 - 3 Months

  • O

    O.P. Jindal Global University

    Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Scikit Learn (Machine Learning Library), Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, NumPy, Matplotlib, Deep Learning, Image Analysis, Machine Learning, Embeddings, Pandas (Python Package), Convolutional Neural Networks, Natural Language Processing, Regression Analysis

    Build toward a degree

    3.9
    Rating, 3.9 out of 5 stars
    ·
    9 reviews

    Beginner · Course · 1 - 3 Months

  • P

    Packt

    Applied Machine Learning and Model Optimization

    Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Algorithms, Predictive Modeling, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Performance Tuning

    Advanced · Course · 1 - 3 Months

  • Status: Top AI Program
    Top AI Program
    D

    DeepLearning.AI

    Supervised Machine Learning: Regression and Classification

    Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Regression Analysis, Unsupervised Learning

    4.9
    Rating, 4.9 out of 5 stars
    ·
    32K reviews

    Beginner · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Practical Machine Learning

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Supervised Learning, Predictive Analytics, Applied Machine Learning, Data Preprocessing, R Programming, Classification Algorithms, Machine Learning, Random Forest Algorithm, Regression Analysis, Exploratory Data Analysis, Data Wrangling

    4.5
    Rating, 4.5 out of 5 stars
    ·
    3.3K reviews

    Mixed · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Linear Algebra for Machine Learning and Data Science

    Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Data Preprocessing, Machine Learning Methods, Advanced Mathematics, Data Manipulation, Applied Mathematics, Mathematical Modeling, Machine Learning, Python Programming, Algebra

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • W

    Wesleyan University

    Machine Learning for Data Analysis

    Skills you'll gain: Classification And Regression Tree (CART), Decision Tree Learning, Model Evaluation, Random Forest Algorithm, Applied Machine Learning, Predictive Analytics, Unsupervised Learning, Machine Learning Algorithms, Machine Learning, Data Analysis, Data Mining, Feature Engineering, Exploratory Data Analysis, Regression Analysis, Statistical Analysis, Python Programming

    4.2
    Rating, 4.2 out of 5 stars
    ·
    328 reviews

    Mixed · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular bayesian methods for machine learning courses

  • Machine Learning on Google Cloud: Google Cloud
  • Data Analytics and Machine Learning for Big Data: Microsoft
  • Probabilistic Graphical Models: A Compact Introduction: Coursera
  • Machine Learning with R: Packt
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Bayesian Statistics: Duke University
  • Machine Learning: O.P. Jindal Global University
  • Applied Machine Learning and Model Optimization: Packt
  • Supervised Machine Learning: Regression and Classification : DeepLearning.AI
  • Practical Machine Learning: Johns Hopkins University

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