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This Building Recommender Systems with Machine Learning and AI course is right for those people who want to learn more about machine learning and AI. In this course, you will get to the knowledge of deep learning, neural networks, Python programming skills, and more machine learning recommendations. Whoever you are, software developers, engineers, computer scientists, or programmers, this hands-on recommendation engine course will be a good boot camp for being proficient in using machine learning techniques and deep learning techniques. Join this Building Recommender Systems with Machine Learning and AI course now, you will get a low price using coupon here.
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About The Recommender Systems Course
This Building Recommender Systems with Machine Learning and AI course will help learners discover and master the recommendation engine development techniques. The popular techniques of deep learning, machine learning, neural networks, and AI are included. This course covers 9.5 hours of on-demand video, 1 article, and 110 lectures. It won’t spend learner much time to pick up the technologies of building recommender systems. If you’re interested in learning the latest recommender system, here will be a good place to get started and you will get a coupon to save much money than ever could.
Requirements & targets:
This Building Recommender Systems with Machine Learning and AI course is perfect for programmers, developers, engineers and more who want to know how to use the machine learning and deep learning techniques for discovering and recommending new products and content. To get started with this course requires students know the background of computer science and have experience with scripting and programming language such as Python. So, if you are complete beginners new to programming and lack of abilities to understand new algorithms, then this course is not right for you.
What you will learn:
The Building Recommender Systems with Machine Learning and AI course gets started with the types of recommenders, you will understand and know the top-n recommender architecture. Next, the course will give you an optional introduction to Python. You will learn how to evaluate recommender systems, how to master a recommender engine framework, how to work with the content-based recommendations and cosine similarity metric. You will also learn everything about the neighborhood-based collaborative filtering skills, matric factorization methods, deep learning, deep learning technology for recommender systems and more. Finally, you will learn Apache spark, real-world challenges, hybrid approaches and practice in case studies.
The Building Recommender Systems with Machine Learning and AI course will give you a good tutorial for learning all things about the recommendation engine technology. After the completion of this course, you will be capable of utilizing the recommender system technology to discover and recommend new products and contents to users. You will thoroughly understand the true recommendation algorithms, you will master the modern development techniques such as matrix factorization, deep learning, machine learning, AI and more. You will be able to ace the real-world challenges that you may encounter in the future. Thus, join this Building Recommender Systems with Machine Learning and AI course today, start you learning journey with an acclaimed instructor.
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