Regístrate ahora

Iniciar sesión

Contraseña perdida

Perdiste tu contraseña? Por favor, introduzca su dirección de correo electrónico. Recibirá un enlace y se creará una nueva contraseña por correo electrónico.

Añadir mensaje

Debe iniciar sesión para añadir notas .

Añadir pregunta

Debe iniciar sesión para hacer una pregunta.

Iniciar sesión

Regístrate ahora

Bienvenido a Scholarsark.com! Su registro le conceda el acceso a la utilización de más características de esta plataforma. Puede hacer preguntas, hacer contribuciones o proporcionar respuestas, ver los perfiles de otros usuarios y mucho más. Regístrate ahora!

Aprendizaje automático & Ciencia de los datos : Python Practical Hands-on

Aprendizaje automático & Ciencia de los datos : Python Practical Hands-on

Precio: $19.99

Interested in the field of Machine Learning? Entonces este curso es para ti!

Designed & Crafted by AI Solution Expert with 15 + years of relevant and hands on experience into Training , Coaching and Development.

  1. Complete Hands-on AI Model Development with Python.

  2. Course Contents are:

    1. Fundamentals of Machine Learning

    2. Machine learning project Life Cycle

    3. Supervised & Unsupervised Learning

    4. Data Pre-Processing

    5. Algorithm Selection

    6. Data Sampling and Cross Validation

    7. Feature Engineering

    8. Model Training and Validation

    9. K -Nearest Neighbor Algorithm

    10. K- Means Algorithm

    11. Accuracy Determination

    12. Visualization using Seaborn

  3. You will be trained to develop various algorithms for supervised & unsupervised methods such as KNN , K-Means , Random Forest, XGBoost model development.

  4. Understanding the fundamentals and core concepts of machine learning model building process with validation and accuracy metric calculation. Determining the optimum model and algorithm.

  5. Cross validation and sampling methods would be understood.

  6. Data processing concepts with practical guidance and code examples provided through the course.

  7. Feature Engineering as critical machine learning process would be explained in easy to understand and yet effective manner.

  8. We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

  9. Además, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

Autor

Acerca de arkadmin

Deja una respuesta