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Advanced Machine Learning with Python Training

  • Training Duration:
  • 5 Days
  • Training Environment:
  • On-site at the Institution
  • In DVA Classrooms
  • Online
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PYTHON 3 PROGRAMMING

About the Training

Advanced Machine Learning with Python Training covers all advanced aspects of the machine learning process using Python. This training includes advanced machine learning topics and teaches the advanced skills necessary for applying these techniques with Python.

The training provides detailed insights into the machine learning algorithms used with Python. It also teaches key topics such as data preprocessing, model selection, and performance evaluation. Participants deepen their knowledge of Python and machine learning through real-world examples and projects.

Additionally, the training covers which tools and technologies can be used in machine learning projects developed with Python. Participants learn how to use essential features such as data processing, model implementation, and performance measurement. They also gain an understanding of how to design and manage machine learning applications developed with Python.

Participants acquire the advanced skills needed before they start designing and executing machine learning projects.

The training program begins with advanced topics in Python and machine learning. Participants learn key concepts such as data preprocessing, model selection, and performance evaluation. It also covers the design and management of Python-based machine learning applications, providing participants with an understanding of Python’s role in these areas. This knowledge forms the foundation for the machine learning projects participants will need to undertake.

The training emphasizes advanced features and components of Python and related machine learning technologies. This gives participants the skills needed for advanced data processing, model implementation, and performance measurement. The course flow covers advanced topics like data processing and managing model performance.

Finally, we provide information on how to develop a machine learning application based on Python. This process includes data preprocessing, model selection, and ultimately, performance evaluation. This knowledge helps participants successfully design and execute machine learning applications using Python.

What Will You Learn?

During the Advanced Machine Learning with Python Training, participants can learn the following:
  • Applying advanced machine learning techniques using the Python programming language.
  • Understanding and implementing topics such as data preprocessing and cleaning, feature selection and engineering, overfitting, and underfitting.
  • Gaining clarity on topics like ensemble methods, deep learning and convolutional neural networks (CNN), reinforcement learning, unsupervised learning, and clustering methods.
  • Understanding and applying concepts such as model selection and optimization, working with noisy and incomplete data, data analytics, and model performance evaluation.
The aim of this training is to elevate participants’ skills and knowledge in the field of machine learning to an advanced level, providing them with more options and tools in their professional toolkit.

Prerequisites

The following prerequisites are required for the Advanced Machine Learning with Python Training:
  • Python Programming Language: The training will use the Python programming language, and participants need to understand the basic concepts of Python.
  • Fundamentals of Machine Learning: Participants should have an understanding of basic concepts and techniques in machine learning.
  • Data Analytics and Statistics: The training will also cover topics related to data analytics and statistics, so participants should have basic knowledge in these areas.
In addition to these prerequisites, having problem-solving and analytical thinking skills will also help participants complete the training effectively.

Who Should Attend?

The following professional groups can participate in the Advanced Machine Learning with Python Training:
  • Machine Learning Specialists: This training will provide professionals working in the field of machine learning with the opportunity to gain more knowledge about advanced techniques and methods.
  • Data Analysts: Data analysts with experience in data analytics and machine learning will have the chance to apply more advanced data analytics techniques and machine learning models.
  • Software Developers: Software developers will have the opportunity to incorporate machine learning concepts and use the Python programming language in their applications.
  • Academics: Researchers working in academia with an interest in machine learning may want to enhance their skills and learn new techniques and methods during the training.
This training can be beneficial for anyone looking to advance their skills and knowledge in the field of machine learning.

Outline

Describing the Structure of Unlabled Data
  • Unsupervised Machine Learning
Recognizing, Clustering and Generating Images, Video Sequences and Motion-capture Data
  • Deep Belief Networks (DBNs)
Reconstructing the Original Input Data from a Corrupted (Noisy) Version
  • Feature Selection and Extraction
  • Stacked Denoising Auto-encoders
Analyzing Visual Images
  • Convolutional Neural Networks
Gaining a Better Understanding of the Structure of Data
  • Semi-Supervised Learning
Understanding Text Data
  • Text Feature Extraction
Building Highly Accurate Predictive Models
  • Improving Machine Learning Results
  • Ensemble Methods

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