Cancel Preloader
First 20 students get 50% discount. Hurry up!

Top Sale Courses

Explore All Courses

Instructor
Level
Language
Rating
Category
Explore
We found 562 courses available for you
Course Meta
2 Months
5

machine learning

  • 8 Lessons
  • 25 Students
Advanced Level
Advanced Machine Learning Algorithms
5
  • 8 Lessons
  • 2 Months
What You’ll Learn?
  • Enhance your comprehension of ensemble methods such as bagging, boosting, and stacking to enhance the efficacy of your models.
  • Apply advanced algorithms such as SVMs and decision trees to classification and regression problems.
  • Learn techniques for assessing the efficacy of models, optimizing hyperparameters, and refining algorithms.
Course Meta
2 Months
3.5

machine learning

  • 8 Lessons
  • 25 Students
Advanced Level
Machine Learning Pipelines and Workflow
3.5
  • 8 Lessons
  • 2 Months
What You’ll Learn?
  • Recognize the significance of data preprocessing and feature engineering in the development of efficient machine learning pipelines.
  • Learn how to deploy models to production, track their performance, and guarantee continuous improvement.
  • Master the entire machine learning project lifecycle, beginning with data collection and preprocessing and ending with model deployment.
Course Meta
2 Months
4.5

machine learning

  • 6 Lessons
  • 25 Students
Advanced Level
Bayesian Machine Learning
4.5
  • 6 Lessons
  • 2 Months
What You’ll Learn?
  • Learn the fundamentals of Bayesian probability theory and how to draw conclusions using Bayes' theorem.
  • Apply Bayesian methods to regression and classification problems to improve your modeling skills.
  • Investigate Bayesian networks and graphical models for representing intricate data relationships.
Course Meta
2 Months
5

machine learning

  • 6 Lessons
  • 25 Students
Advanced Level
Machine Learning for Anomaly Detection
5
  • 6 Lessons
  • 2 Months
What You’ll Learn?
  • Learn about numerous anomaly detection algorithms and how to identify anomalous data patterns.
  • Learn techniques for detecting anomalies in time series data, which are crucial for applications such as fraud detection.
  • Examine anomaly detection's real-world applications in industries such as manufacturing, finance, and cybersecurity.
Course Meta
2 Months
3.5

machine learning

  • 6 Lessons
  • 25 Students
Advanced Level
Ethical Considerations in Machine Learning
3.5
  • 6 Lessons
  • 2 Months
What You’ll Learn?
  • Learn the ethical challenges associated with bias in machine learning models and the strategies for ensuring impartiality.
  • Investigate the significance of privacy in machine learning, as well as methods for protecting sensitive data during training and deployment.
  • Explore the openness and responsibility of machine learning, confronting issues of model interpretability and accountable AI development.