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Titlebook: Building Machine Learning and Deep Learning Models on Google Cloud Platform; A Comprehensive Guid Ekaba‘Bisong Book 2019 Ekaba Bisong 2019

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樓主: antithetic
21#
發(fā)表于 2025-3-25 05:33:30 | 只看該作者
The Google Cloud SDK and Web CLIGCP provides a command-line interface (CLI) for interacting with cloud products and services. GCP resources can be accessed via the web-based CLI on GCP or by installing the Google Cloud software development kit (SDK) on your local machine to interact with GCP via the local command-line terminal.
22#
發(fā)表于 2025-3-25 10:26:05 | 只看該作者
23#
發(fā)表于 2025-3-25 15:31:01 | 只看該作者
NumPyNumPy is a Python library optimized for numerical computing. It bears close semblance with MATLAB and is equally as powerful when used in conjunction with other packages such as SciPy for various scientific functions, Matplotlib for visualization, and Pandas for data analysis. NumPy is short for numerical python.
24#
發(fā)表于 2025-3-25 19:46:09 | 只看該作者
Urszula Strawinska-Zanko,Larry S. Liebovitch has guarantees of scalability (can store increasingly large data objects), consistency (the most updated version is served on request), durability (data is redundantly placed in separate geographic locations to eliminate loss), and high availability (data is always available and accessible).
25#
發(fā)表于 2025-3-25 19:58:39 | 只看該作者
26#
發(fā)表于 2025-3-26 03:27:11 | 只看該作者
27#
發(fā)表于 2025-3-26 08:22:31 | 只看該作者
Manoj Sahni,José M. Merigó,Ritu Sahnig data, dealing with missing data, reshaping the dataset, and massaging the data by slicing, indexing, inserting, and deleting data variables and records. Pandas also has an important . functionality for aggregating data for defined conditions?– useful for plotting and computing data summaries for exploration.
28#
發(fā)表于 2025-3-26 10:00:22 | 只看該作者
29#
發(fā)表于 2025-3-26 14:49:20 | 只看該作者
Generalized KKM Mapping Theoremsild your learning model with data at rest (batch learning), and the other is when the data is flowing in streams into the learning algorithm (online learning). This flow can be as individual sample points in your dataset, or it can be in small batch sizes. Let’s briefly discuss these concepts.
30#
發(fā)表于 2025-3-26 18:25:56 | 只看該作者
Adeeba Umar,Ram Naresh Saraswatn iterative optimization algorithm because, in a stepwise looping fashion, it tries to find an approximate solution by basing the next step off its present step until a terminating condition is reached that ends the loop.
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