{"id":1481,"date":"2019-08-14T10:09:18","date_gmt":"2019-08-14T10:09:18","guid":{"rendered":"https:\/\/www.dboktechnologies.com\/?p=1481"},"modified":"2020-08-28T20:34:50","modified_gmt":"2020-08-28T20:34:50","slug":"relates-to-ml-understand-sentiments","status":"publish","type":"post","link":"https:\/\/www.dboktechnologies.com\/relates-to-ml-understand-sentiments\/","title":{"rendered":"Relates to ML ( understand sentiments )"},"content":{"rendered":"
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The basic procedure of machine learning is to give preparation data to a learning algorithm. The learning algorithm then generates a new set of rules, based on inferences from the data. This is in spirit generate a new algorithm, formally referred to as the machine learning model. By using different training data, the same learning algorithm could be used to generate different models. For example, the same type of learning algorithm could be used to teach the computer how to translate languages or predict the stock market.<\/p>\n
Inferring new instructions from data is the core strength of machine learning. It also highlights the critical role of data: the more data available to train the algorithm, the more it learns. In fact, many recent advances in AI have not been due to radical innovations in learning algorithms, but rather by the enormous amount of data enabled by the Internet.<\/p>\n
How machines learn:<\/b><\/p>\n
Although a machine learning model may apply a mix of different techniques, the methods for learning can typically be categorized as three general types:<\/p>\n
Why now?<\/b><\/p>\n
Machine learning is not new. Many of the learning algorithms that spurred new interest in the field, such as neural networks, are based on decades-old research. The current growth in AI and machine learning is tied to developments in three important areas:<\/p>\n
Key Considerations<\/b><\/p>\n
As machine learning algorithms are used in more and more products and services, there are some serious factors must be considered when addressing AI, particularly in the context of people\u2019s trust in the Internet:<\/p?<\/p>\n
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