| Sumario: | More than 7.5 Hours of Video Instruction Overview Nearly every company in the world is evaluating its digital strategy and looking for ways to capitalize on the promise of digitization. Big data analytics and machine learning are central to this strategy. Understanding the fundamentals of data processing and artificial intelligence is becoming required knowledge for executives, digital architects, IT administrators, and operational telecom (OT) professionals in nearly every industry. In Data Analytics and Machine Learning Fundamentals LiveLessons , experienced CCIEs Robert Barton and Jerome Henry provide more than 7 1/2 hours of personal instruction exploring the principles of big data analytics, supervised learning, unsupervised learning, and neural networks. In addition to delving into the fundamental concepts, Barton and Henry address sample big data and machine learning use cases in different industries and present demos featuring the most common tools (such as Hadoop, TensorFlow, Matlab/Octave, R, and Python) in various fields used by data scientists and researchers. At the conclusion of this video course, you will be armed with knowledge and application skills required to become proficient in articulating big data analytics and machine learning principles and possibilities. Skill Level Beginner to intermediate data analytics/machine learning knowledge Learn How To * Understand how static and real-time streaming data is collected, analyzed, and used * Understand the key tools and methods that enable machines to learn and mimic human thinking * Bring together unstructured data in preparation for analysis and visualization * Compare and contrast the various big data architectures * Apply supervised learning/linear regression, data fitting, and reinforcement learning to machines to yield the information results you’re looking for * Apply classification techniques to machine learning to better analyze your data * Exploit the benefits of unsupervised learning to glean data you didn’t even know you were looking for * Understand how artificial neural networks (ANNs) perform deep learning with surprising (and useful) results * Apply principal components analysis (PCA) to improve the management of data analysis * Understand the key approaches to implementing machine learning on real systems and the considerations you must make when undertaking a machine learning project Who Should Take This Course * Anyone who wants to learn about machine learni...
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