Launching into Machine Learning
This article explores the history of machine learning and examines why neural networks are so successful in solving a wide range of problems. It provides an introduction to the field of machine learning and its current applications. ▼
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Course Feature
Cost:
Free Trial
Provider:
Pluralsight
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
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Updated in [March 06th, 2023]
This course, Launching into Machine Learning, provides an introduction to the fundamentals of machine learning. Participants will learn how to create datasets that permit generalization and discuss methods of doing so in a repeatable way to support experimentation. Topics covered include data pre-processing, feature engineering, model selection, and model evaluation. Participants will gain hands-on experience with popular machine learning algorithms and libraries such as Scikit-Learn and TensorFlow. By the end of the course, participants will have the skills and knowledge to apply machine learning to their own projects.
[Applications]
The application of this course is to help individuals gain a better understanding of machine learning and how to create datasets that can be used for experimentation. After completing this course, individuals should be able to create datasets that are suitable for machine learning experiments, as well as understand the importance of repeatability and generalization. Additionally, they should be able to identify and apply appropriate methods for creating datasets that are suitable for machine learning experiments.
[Career Paths]
1. Data Scientist: Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use machine learning algorithms to develop predictive models and create data-driven solutions. With the increasing demand for data-driven decision making, the demand for Data Scientists is expected to grow significantly in the coming years.
2. Machine Learning Engineer: Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use a variety of techniques, such as supervised and unsupervised learning, to create models that can be used to solve real-world problems. With the increasing demand for automation and AI-driven solutions, the demand for Machine Learning Engineers is expected to grow significantly in the coming years.
3. Artificial Intelligence Engineer: Artificial Intelligence Engineers are responsible for designing, developing, and deploying AI-driven solutions. They use a variety of techniques, such as deep learning and natural language processing, to create AI-driven solutions that can be used to solve real-world problems. With the increasing demand for automation and AI-driven solutions, the demand for Artificial Intelligence Engineers is expected to grow significantly in the coming years.
4. Business Intelligence Analyst: Business Intelligence Analysts are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use machine learning algorithms to develop predictive models and create data-driven solutions. With the increasing demand for data-driven decision making, the demand for Business Intelligence Analysts is expected to grow significantly in the coming years.
[Education Paths]
1. Bachelor's Degree in Computer Science: A Bachelor's Degree in Computer Science provides a comprehensive overview of the fundamentals of computer science, including programming, algorithms, data structures, and software engineering. It also covers topics such as artificial intelligence, machine learning, and robotics. This degree is ideal for those looking to pursue a career in the field of machine learning, as it provides the necessary foundation for understanding the concepts and techniques used in the field. Additionally, the degree provides the opportunity to specialize in a particular area of machine learning, such as natural language processing or computer vision.
2. Master's Degree in Artificial Intelligence: A Master's Degree in Artificial Intelligence provides a more in-depth look at the field of machine learning. It covers topics such as deep learning, reinforcement learning, and neural networks. This degree is ideal for those looking to pursue a career in the field of machine learning, as it provides the necessary foundation for understanding the concepts and techniques used in the field. Additionally, the degree provides the opportunity to specialize in a particular area of machine learning, such as natural language processing or computer vision.
3. Doctoral Degree in Machine Learning: A Doctoral Degree in Machine Learning provides an even more in-depth look at the field of machine learning. It covers topics such as deep learning, reinforcement learning, and neural networks. This degree is ideal for those looking to pursue a career in the field of machine learning, as it provides the necessary foundation for understanding the concepts and techniques used in the field. Additionally, the degree provides the opportunity to specialize in a particular area of machine learning, such as natural language processing or computer vision.
The field of machine learning is rapidly evolving, and the demand for professionals with expertise in this area is growing. As such, pursuing a degree in machine learning is a great way to stay ahead of the curve and gain the skills necessary to succeed in the field. Additionally, the degree provides the opportunity to specialize in a particular area of machine learning, such as natural language processing or computer vision, which can help to further develop one's career.
Pros & Cons
Gradient descent and loss function concepts explained well
Engaging lectures
Lively and engaging presentation
Good balance between complexity and easetopass
Poor labs
Complicated concepts expected to be known
Proofreading and UI issues
Too much focus on philosophy
Slow labs VMs
Difficult to understand speaker
Course Provider
Provider Pluralsight's Stats at AZClass
Pluralsight ranked 16th on the Best Medium Workplaces List.
Pluralsight ranked 20th on the Forbes Cloud 100 list of the top 100 private cloud companies in the world.
Pluralsight Ranked on the Best Workplaces for Women List for the second consecutive year.
AZ Class hope that this free trial Pluralsight course can help your Machine Learning skills no matter in career or in further education. Even if you are only slightly interested, you can take Launching into Machine Learning course with confidence!
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