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Machine Learning Algorithms is for current and ambitious machine learning specialists looking to implement solutions to real-world machine learning problems. It talks entirely about the various applications of machine and deep learning techniqu
machine learning algorithms are behind many modern technologies we use daily. They help in automating tasks, providing personalized experiences, and even in complex applications like predicting diseases or stock market trends.
the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the correspondingsmart and automatedapplications, the knowledge of artificial intelli...
learning in a short time once a system is deployed. In those applications, organizations prefer RL algorithms that can learn good policy after only a few switches or deployments. Yet, a gap still remains between existing algo...
本书为了解机器学习提供了一种独特的途径。书中包含了新颖、直观而又严谨的基本概念描述,它们是研究课题、制造产品、修补漏洞以及实践不可或缺的部分。本书按照几何直觉、算法思想和实际应用(纵贯计算机视觉、自然语言处理、经济学、神经科学、推荐系统、物理学和生物学...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms. ...
The major class of machine learning and deep learning methods come under inductive reasoning where essentially, missing pieces of information are interpolated based on existing data through numerical transformations. However, today AI is mostly identified with deduction systems while it is actually a ...
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics. ...
Apply machine learning techniques to financial applications Process, analyze, and engineer features from large financial time series data sets, and create predictive financial time series models by training and validating machine learning algorithms. For general information on machine learning, seeMachine L...