Machine Learning & Deep Learning : Python Practical Hands-on

Code, Develop, Validate & Deploy Machine Learning & Keras Deep Learning Neural Network Models.

Bullstrack Bullstrack
Feb 28, 2023 - 21:38 Updated: Feb 27, 2023 - 23:11
4.5 0 11
Machine Learning & Deep Learning : Python Practical Hands-on
Machine Learning & Deep Learning : Python Practical Hands-on

Machine Learning & Deep Learning : Python Practical Hands-on udemy course

Code, Develop, Validate & Deploy Machine Learning & Keras Deep Learning Neural Network Models.

What you'll learn:

  • Develop complete machine learning/deep learning solutions in Python
  • Write and test Python code interactively using Jupyter notebooks
  • Build, train, and test deep learning models using the popular Tensorflow 2 and Keras APIs
  • Neural network fundamentals by building models from the ground up using only basic Python
  • Manipulate multidimensional data using NumPy
  • Load and transform structured data using Pandas
  • Build high quality, eye catching visualizations with Matplotlib
  • Reduce training time using free Google Colab GPU instances in the cloud
  • Recognize images using Convolutional Neural Networks (CNNs)
  • Make recommendations using collaborative filtering
  • Detect fraud using autoencoders
  • Improve model accuracy and eliminate overfitting

Requirements:

  • Basic software development skills
  • Basic high school math, such as trigonometry and algebra

Description:

Interested in the field of Machine Learning? Then this course is for you!

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. Understand Machine Learning in depth and in simple process.

    2. Fundamentals of Machine Learning

    3. Understand the Deep Learning Neural Nets with Practical Examples.

    4. Understand Image Recognition and Auto Encoders.

    5. Machine learning project Life Cycle

    6. Supervised & Unsupervised Learning

    7. Data Pre-Processing

    8. Algorithm Selection

    9. Data Sampling and Cross Validation

    10. Feature Engineering

    11. Model Training and Validation

    12. K -Nearest Neighbor Algorithm

    13. K- Means Algorithm

    14. Accuracy Determination

    15. 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. Moreover, 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.

Who this course is for:

Course Details:

  • 11 hours on-demand video
  • 2 articles
  • 6 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of completion

Machine Learning & Deep Learning : Python Practical Hands-on udemy free download

Code, Develop, Validate & Deploy Machine Learning & Keras Deep Learning Neural Network Models.

Demo Link: https://www.udemy.com/course/machine-learning-data-science-python-practical-hands-on/

Login to Download  
Tags: