ML Algorithms: Supervised Learning Tip to Tail

ML Algorithms: Supervised Learning Tip to Tail

(0 reviews)
Share icon

This course concentrates on the fundamentals of machine learning, including decision trees, k-nearest neighbors, and support vector machines. It addresses data preparation and production challenges and requires a rudimentary understanding of Python, linear algebra, and statistics.

Key AI Functions:Machine Learning,Supervised Learning,Decision Tree

Description for ML Algorithms: Supervised Learning Tip to Tail

Features of Course

  • The course delves into the fundamentals of a machine learning project, with a particular emphasis on support vector machines, decision trees, and k-nearest neighbors for the purpose of conducting real-world case studies.
  • It instructs on the comparison of data preparation procedures and the resolution of production challenges in the context of applied machine learning.
  • A fundamental comprehension of linear algebra and statistics, as well as a basic understanding of Python programming, are necessary.
  • This is the second course in the Applied Machine Learning Specialization, which is offered by the Alberta Machine Intelligence Institute and Coursera.
  • Level: Intermediate

    Certification Degree: Yes

    Languages the Course is Available: 22

    Offered by: On Coursera provided by Alberta Machine Intelligence Institute

    Duration: 9 hours (approximately)

    Schedule: Flexible

    Reviews for ML Algorithms: Supervised Learning Tip to Tail

    0 / 5

    from 0 reviews

    Ease of Use

    Ease of Customization

    Intuitive Interface

    Value for Money

    Support Team Responsiveness

    Alternative Tools for ML Algorithms: Supervised Learning Tip to Tail

    icon
    Paid

    The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.

    #research #marketing
    icon

    Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.

    #Artificial Intelligence (AI) #Data Science
    icon

    Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.

    #Artificial Intelligence (AI) #Python Programming
    icon

    Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world

    #Tensorflow #Machine Learning
    icon

    Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.

    #Generative AI #Large Language Models
    icon

    Learn the significance, use cases, history, and pros and cons of generative AI in a business context, with a focus on its relationship to machine learning and services at Amazon.

    #Generative AI #Amazon Web Services
    icon

    Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.

    #Python Programming #Machine Learning
    icon

    The "Introduction to Vertex AI" course provides a four-hour, practical, and fundamental overview of Vertex AI, ideal for professionals and enthusiasts aiming to leverage AI effectively.

    #Critical Thinking #MLOps (Machine Learning Operations)
    icon

    Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.

    #Logistic Regression #Unsupervised Learning
    icon

    Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.

    #Artificial Intelligence #Python (Programming Language)
    icon