Google fit dataset

Walmart. Walmart challenges participants to accurately predict the sales of 111 potentially weather-sensitive products (like umbrellas, bread, and milk) around the time of major weather events at 45 of their retail locations.

The Google Public Data Explorer makes large datasets easy to explore, visualize and communicate. As the charts and maps animate over time, the changes in the world become easier to understand. You ...

Pre-trained models and datasets built by Google and the community Tools Ecosystem of tools to help you use TensorFlow ... tf.data.Dataset( variant_tensor ) Used in ... python keras 2 fit_generator large dataset multiprocessing. By Afshine Amidi and Shervine Amidi Motivation. Have you ever had to load a dataset that was so memory consuming that you wished a magic trick could seamlessly take care of that? Large datasets are increasingly becoming part of our lives, as we are able to harness an ever-growing ...

vis.js community edition * A dynamic, browser based visualization library. The library is designed to be easy to use, to handle large amounts of dynamic data, and to enable manipulation of and interaction with the data.

Mar 17, 2017 · For any imbalanced data set, if the event to be predicted belongs to the minority class and the event rate is less than 5%, it is usually referred to as a rare event. Example of imbalanced data. Let’s understand this with the help of an example. Ex: In an utilities fraud detection data set you have the following data: Total Observations = 1000 Nov 02, 2018 · Posted by Jacob Devlin and Ming-Wei Chang, Research Scientists, Google AI Language One of the biggest challenges in natural language processing (NLP) is the shortage of training data. Because NLP is a diversified field with many distinct tasks, most task-specific datasets contain only a few thousand or a few hundred thousand human-labeled ... .

Decision Tree Classifier implementation in R. The decision tree classifier is a supervised learning algorithm which can use for both the classification and regression tasks.

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Google Play services 7.5 introduces the following new Google Fit features: Distance traveled and calories expended computations are available for subscription. The Fit platform starts tracking... .

Oct 09, 2019 · The dataset will have a data source ID of derived:com.google.:com.google.android.gms:aggregated: aggregateBy[]. dataSourceId: string: A data source ID to aggregate. Mutually exclusive of dataTypeName. Only data from the specified data source ID will be included in the aggregation. The dataset in the response will have the same data source ID.

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Dataset identifier that is a composite of the minimum data point start time and maximum data point end time represented as nanoseconds from the epoch. The ID is formatted like: " startTime - endTime " where startTime and endTime are 64 bit integers. Mar 17, 2017 · For any imbalanced data set, if the event to be predicted belongs to the minority class and the event rate is less than 5%, it is usually referred to as a rare event. Example of imbalanced data. Let’s understand this with the help of an example. Ex: In an utilities fraud detection data set you have the following data: Total Observations = 1000 , , , , , , , , , , , , .

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The Google Public Data Explorer makes large datasets easy to explore, visualize and communicate. As the charts and maps animate over time, the changes in the world become easier to understand. You ...

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  • Sep 16, 2018 · I have some observations about the accuracy of this app vis-a-vis Strava for the same places. Figure 1: Google Fit Image Figure 2: Strava Image for the same location Figure 3 : Google Fit Image when I tried to went back the same path The Strava im... , , , .
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