ML projects
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Avoiding Misleading Data in Google Trends for ML
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Google Trends data can be misleading when used in time series or machine learning projects due to its normalization process, which sets the maximum value to 100 for each query window independently. This means that the meaning of the value 100 changes with every date range, leading to potential inaccuracies when sliding windows or stitching data together without proper adjustments. A robust method is needed to create a comparable daily series, as naive approaches may result in models trained on non-comparable numbers. By understanding the normalization behavior and employing a more careful approach, it's possible to achieve a more accurate analysis of Trends data, which is crucial for reliable machine learning outcomes.
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NextToken: Simplifying AI and ML Projects
Read Full Article: NextToken: Simplifying AI and ML Projects
NextToken is an AI agent designed to simplify the process of working on AI, ML, and data projects by handling tedious tasks such as environment setup, code debugging, and data cleaning. It assists users by configuring workspaces, fixing logic issues in code, explaining the math behind libraries, and automating data cleaning and model training processes. By reducing the time spent on these tasks, NextToken allows engineers to focus more on building models and less on troubleshooting, making AI and ML projects more accessible to beginners. This matters because it lowers the barrier to entry for those new to AI and ML, encouraging more people to engage with and complete their projects.