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Titlebook: Machine Learning Using R; With Time Series and Karthik Ramasubramanian,Abhishek Singh Book 2019Latest edition Karthik Ramasubramanian and A

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發(fā)表于 2025-3-25 05:08:39 | 只看該作者
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發(fā)表于 2025-3-26 02:49:08 | 只看該作者
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發(fā)表于 2025-3-26 07:47:18 | 只看該作者
Machine Learning Theory and Practice,he games like Go and Jeopardy against humans, ML is pervasive. The availability and ease of collecting data coupled with high computing power has made this field even more conducive to researchers and businesses to explore data-driven solutions for some of the most challenging problems. This has led
28#
發(fā)表于 2025-3-26 10:21:23 | 只看該作者
Machine Learning Model Evaluation,rmance and decide whether to go ahead with the model or revisit all our previous steps as described in the PEBE, our machine learning process flow, in Chapter .. In many cases, we may even discard the complete model based on the performance metrics. This phase of the PEBE plays a very critical role
29#
發(fā)表于 2025-3-26 15:52:30 | 只看該作者
Model Performance Improvement,lso play the role of thresholds to decide whether the model can be put into actual decision making systems or needs improvements. In the previous chapter, we discussed some performance metrics for our continuous and discrete cases. In this chapter, we discuss how changing the modeling process can he
30#
發(fā)表于 2025-3-26 17:30:23 | 只看該作者
Time Series Modeling,t have high correlation with time and considerable part of the variance is due to changing times. The introduction to time series analysis will help you understand how to count time-dependent variations.
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