Advanced Machine Learning with Python
Description
In this intensive one-day training, "Advanced Machine Learning in Python", experienced data scientists and analysts will dive deep into the world of Deep Learning, with a focus on training Neural Networks. The training covers both practical insights and theoretical foundations of machine learning. By the end of the day, you'll be equipped to build and train a model for image analysis. The course emphasizes combining theory with practice, featuring a hands-on project where you will set up, train, and evaluate a neural network while understanding the advantages and limitations of machine learning.
This course is designed for experienced data scientists and analysts who:
- Want to understand how Deep Learning and Neural Networks work, both theoretically and practically.
- Wish to build and train their own machine learning model for image recognition or similar applications.
- Seek deeper insight into the strengths and weaknesses of machine learning and its appropriate use cases.
After completing this training, you will:
- Understand the theoretical foundations of Deep Learning and Neural Networks.
- Be able to set up a complete machine learning project in Python.
- Have the ability to analyze images using a self-built and trained model.
- Gain insight into the strengths and weaknesses of machine learning and know how to apply this knowledge to your own projects.
Prerequisites to Attend "Advanced Machine Learning with Python"
Participants should:
- Be proficientin Python and data analysis.
- Have experience with libraries such as NumPy, pandas, and matplotlib.
Topics
- Introduction to Deep Learning and Neural Networks.
- Data preprocessing and augmentation for image datasets.
- Setting up and training a Neural Network: hyperparameter tuning, loss functions, and optimization algorithms.
- Hands-on project: Training a model to analyze images.
- Evaluating model performance and discussing the practical applicability of machine learning.
Course Materials
The training includes carefully curated learning materials and practical case studies. All necessary files and datasets will be provided in advance, allowing you to start immediately.
Available dates
There are currently no scheduled dates available. Please contact us for options.