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Applied Machine Learning
Coursera Certificate 0

Applied Machine Learning

About this course

This specialization is intended for post-graduate students seeking to develop practical machine-learning skills applicable across various domains. Through three comprehensive courses, learners will explore core techniques including supervised learning, ensemble methods, regression analysis, unsupervised learning, and neural networks. The courses emphasize hands-on learning, providing you with the opportunity to apply machine learning to real-world problems like image classification, data feature extraction, and model optimization. You will dive into advanced topics such as convolutional neural networks (CNNs), reinforcement learning, and apriori analysis, learning to leverage the PyTorch framework for deep learning tasks. By the end of the specialization, you will be well-equipped to handle complex machine learning challenges in fields like computer vision and data processing, making you a valuable asset in industries requiring advanced predictive modeling, AI-driven solutions, and data-driven decision-making. This specialization is designed to build both theoretical knowledge and practical skills to thrive in the ever-evolving tech landscape.

A

90/100

CourseAsk score

What the provider tells you
39/45
Who stands behind it
35/35
How complete the listing is
16/20

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What you'll learn

  • core techniques of supervised and unsupervised learning
  • ensemble methods
  • regression analysis
  • hands-on application of machine learning to real-world problems
  • understanding convolutional neural networks (CNNs)
  • reinforcement learning concepts
  • data feature extraction
  • model optimization using PyTorch

Course objectives

  • build both theoretical knowledge and practical skills in machine learning
  • prepare for challenges in computer vision and data processing
  • enable data-driven decision-making in various industries
$49.00

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