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  • Statistical Classification

Results for "statistical classification"


  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Geliştiriciler için Üretken Yapay Zeka

    Skills you'll gain: Responsible AI, Prompt Engineering, AI Security, Google Gemini, Gemini, Prompt Patterns, Generative AI, Embeddings, Multimodal Prompts, AI Product Strategy, Model Deployment, Vector Databases, Keras (Neural Network Library), Generative Model Architectures, Cloud Security, Data Ethics, Application Security, Natural Language Processing, Recurrent Neural Networks (RNNs), Machine Learning

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Reproducibility in Cancer Informatics

    Skills you'll gain: Code Review, GitHub, Git (Version Control System), Version Control, Docker (Software), Software Development Tools, Continuous Integration, Containerization, Bioinformatics, Informatics, Automation, Data Analysis, R Programming

    Advanced · Course · 1 - 3 Months

  • Status: Preview
    Preview
    D

    DeepLearning.AI

    AI、機械学習、ディープラーニングのための TensorFlow 入門

    Skills you'll gain: Tensorflow, Computer Vision, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    D

    Duke University

    Beginning Llamafile for Local Large Language Models (LLMs)

    Skills you'll gain: LLM Application, Large Language Modeling, Model Deployment, Embeddings, Application Programming Interface (API), Restful API, Natural Language Processing, Command-Line Interface, Machine Learning

    Beginner · Course · 1 - 4 Weeks

  • G

    Google Cloud

    Introduction to Computer Vision with TensorFlow

    Skills you'll gain: Model Evaluation, Tensorflow, Convolutional Neural Networks, Computer Vision, Keras (Neural Network Library), Development Environment, Image Analysis, Machine Learning, Deep Learning, Data Persistence, Artificial Neural Networks

    5
    Rating, 5 out of 5 stars
    ·
    6 reviews

    Beginner · Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Pearson

    Data Science Fundamentals Part 2: Unit 1

    Skills you'll gain: Exploratory Data Analysis, Matplotlib, Box Plots, Data Analysis, Data Visualization, Descriptive Statistics, Scatter Plots, Data Visualization Software, Histogram, Seaborn, Statistical Analysis, Correlation Analysis, Statistical Methods

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Pearson

    Learning Deep Learning: Unit 2

    Skills you'll gain: Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Tensorflow, Transfer Learning, Natural Language Processing, Embeddings, Image Analysis, Deep Learning, Computer Vision, Time Series Analysis and Forecasting

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Advanced Machine Learning, Big Data, and Deep Learning

    Skills you'll gain: Apache Spark, PySpark, Model Evaluation, Data Preprocessing, Keras (Neural Network Library), Transfer Learning, Deep Learning, Tensorflow, A/B Testing, Data Ethics, Convolutional Neural Networks, Machine Learning Software, Data Cleansing, Machine Learning, Recurrent Neural Networks (RNNs), MLOps (Machine Learning Operations), Artificial Intelligence, Dimensionality Reduction

    Advanced · Course · 1 - 3 Months

  • C

    Coursera

    Machine/Deep Learning for Mining Quality Prediction-Enhanced

    Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Preprocessing, Regression Analysis, Applied Machine Learning, Scikit Learn (Machine Learning Library), Data Analysis, Matplotlib, Random Forest Algorithm, Machine Learning, Data Visualization, Decision Tree Learning, Artificial Neural Networks, Deep Learning, Python Programming

    4.9
    Rating, 4.9 out of 5 stars
    ·
    7 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Practical Methodology and Ethics in AI

    Skills you'll gain: Responsible AI, Data Ethics, Deep Learning, Model Deployment, Debugging, Artificial Intelligence, Machine Learning, Ethical Standards And Conduct, Model Evaluation, Applied Machine Learning, Social Impact, Unstructured Data, Data-Driven Decision-Making, Information Privacy, Case Studies

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    S

    Sungkyunkwan University

    Recommender Systems

    Skills you'll gain: Scalability, Deep Learning, AI Personalization, Data Mining, Data Processing, Machine Learning, Machine Learning Algorithms, Algorithms, Model Evaluation

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    IPOs & FPOs: Apply Valuation Strategies

    Skills you'll gain: Investment Banking, Business Valuation, Equities, Underwriting, Capital Markets, Securities (Finance), Entrepreneurial Finance, Financial Analysis, Financial Modeling, Fundraising, Market Dynamics

    4.9
    Rating, 4.9 out of 5 stars
    ·
    14 reviews

    Mixed · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular statistical classification courses

  • Geliştiriciler için Üretken Yapay Zeka: Google Cloud
  • Advanced Reproducibility in Cancer Informatics: Johns Hopkins University
  • AI、機械学習、ディープラーニングのための TensorFlow 入門: DeepLearning.AI
  • Beginning Llamafile for Local Large Language Models (LLMs): Duke University
  • Introduction to Computer Vision with TensorFlow: Google Cloud
  • Data Science Fundamentals Part 2: Unit 1: Pearson
  • Learning Deep Learning: Unit 2: Pearson
  • Advanced Machine Learning, Big Data, and Deep Learning: Packt
  • Machine/Deep Learning for Mining Quality Prediction-Enhanced: Coursera
  • Practical Methodology and Ethics in AI: Johns Hopkins University

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