標(biāo)題: Titlebook: Building Machine Learning and Deep Learning Models on Google Cloud Platform; A Comprehensive Guid Ekaba‘Bisong Book 2019 Ekaba Bisong 2019 [打印本頁] 作者: antithetic 時(shí)間: 2025-3-21 19:04
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform影響因子(影響力)
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform影響因子(影響力)學(xué)科排名
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform網(wǎng)絡(luò)公開度
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform被引頻次
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform被引頻次學(xué)科排名
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform年度引用
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform年度引用學(xué)科排名
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform讀者反饋
書目名稱Building Machine Learning and Deep Learning Models on Google Cloud Platform讀者反饋學(xué)科排名
作者: 鎮(zhèn)痛劑 時(shí)間: 2025-3-21 22:02
A. Toleukhanov,M. Panfilov,A. Kaltayev take advantage of Google’s state-of-the-art fiber optic powered network capabilities to offer fast and high-performance machines that can scale based on usage and automatically deal with issues of load balancing.作者: 缺乏 時(shí)間: 2025-3-22 02:12 作者: 賞心悅目 時(shí)間: 2025-3-22 05:53 作者: amplitude 時(shí)間: 2025-3-22 09:19 作者: 做事過頭 時(shí)間: 2025-3-22 13:55 作者: 桉樹 時(shí)間: 2025-3-22 19:51 作者: Jingoism 時(shí)間: 2025-3-23 00:00
Gunjan Rani,Arpit Dwivedi,Ganga Ram Gautam for example, that we want a computer to perform the task of recognizing faces in an image. One will realize that it is incredibly complicated, if not impossible to develop a precise instruction set that will satisfactorily perform this task. However, by drawing from the observation that humans impr作者: MAOIS 時(shí)間: 2025-3-23 05:04
Shubhashree Bebarta,Mahendra Kumar Jenaies of learning are the supervised, unsupervised, and reinforcement learning schemes. In this chapter, we will go over supervised learning schemes in detail and also touch upon unsupervised and reinforcement learning schemes to a lesser extent.作者: Delirium 時(shí)間: 2025-3-23 05:42
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.作者: 供過于求 時(shí)間: 2025-3-23 12:01
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.作者: 有限 時(shí)間: 2025-3-23 16:21 作者: 壕溝 時(shí)間: 2025-3-23 19:32 作者: FAR 時(shí)間: 2025-3-23 22:52 作者: Defraud 時(shí)間: 2025-3-24 03:42
Thermodynamic Concepts Out of Equilibrium,Google Cloud Platform offers a wide range of services for securing, storing, serving, and analyzing data. These cloud services form a secure cloud perimeter for data, where different operations and transformations can be carried out on the data without it ever leaving the cloud ecosystem.作者: 舔食 時(shí)間: 2025-3-24 10:35 作者: NUDGE 時(shí)間: 2025-3-24 12:32
Reference Frames, Body Motion and Notation,Google Colaboratory more commonly referred to as “Google Colab” or just simply “Colab” is a research project for prototyping machine learning models on powerful hardware options such as GPUs and TPUs. It provides a serverless Jupyter notebook environment for interactive development. Google Colab is free to use like other G Suite products.作者: 注意到 時(shí)間: 2025-3-24 17:18
https://doi.org/10.1007/978-3-030-95136-8NumPy 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.作者: Congeal 時(shí)間: 2025-3-24 21:40 作者: manifestation 時(shí)間: 2025-3-25 02:42 作者: 草本植物 時(shí)間: 2025-3-25 05:33
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.作者: septicemia 時(shí)間: 2025-3-25 10:26 作者: 大漩渦 時(shí)間: 2025-3-25 15:31
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.作者: 我邪惡 時(shí)間: 2025-3-25 19:46
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).作者: Legion 時(shí)間: 2025-3-25 19:58 作者: EVEN 時(shí)間: 2025-3-26 03:27 作者: AMOR 時(shí)間: 2025-3-26 08:22
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.作者: Lipoprotein(A) 時(shí)間: 2025-3-26 10:00 作者: 相符 時(shí)間: 2025-3-26 14:49
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.作者: Countermand 時(shí)間: 2025-3-26 18:25
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.作者: Petechiae 時(shí)間: 2025-3-27 00:16 作者: meritorious 時(shí)間: 2025-3-27 01:53
Google Cloud Storage (GCS) 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).作者: 逃避責(zé)任 時(shí)間: 2025-3-27 09:04 作者: 分散 時(shí)間: 2025-3-27 11:53
JupyterLab Notebooksrelevant software packages for carrying out analytics and modeling tasks. It also makes available high-performance computing TPU and GPU processing capabilities at a single click. These VMs expose a JupyterLab notebook environment for analyzing data and designing machine learning models.作者: 擁擠前 時(shí)間: 2025-3-27 16:57 作者: 期滿 時(shí)間: 2025-3-27 19:37
Principles of Learningies of learning are the supervised, unsupervised, and reinforcement learning schemes. In this chapter, we will go over supervised learning schemes in detail and also touch upon unsupervised and reinforcement learning schemes to a lesser extent.作者: OMIT 時(shí)間: 2025-3-27 23:42
Batch vs. Online Learningild 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.作者: Heart-Attack 時(shí)間: 2025-3-28 04:52
Optimization for Machine Learning: Gradient Descentn 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.作者: 事情 時(shí)間: 2025-3-28 09:29
Building Machine Learning and Deep Learning Models on Google Cloud PlatformA Comprehensive Guid作者: SENT 時(shí)間: 2025-3-28 13:02 作者: Thymus 時(shí)間: 2025-3-28 18:09 作者: REIGN 時(shí)間: 2025-3-28 21:07
Book 2019rning and Deep Learning Models on Google Cloud Platform.?is dividedinto eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and p作者: BOON 時(shí)間: 2025-3-28 23:57
s you with skills to build and deploy large-scale learning m.Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to作者: FILTH 時(shí)間: 2025-3-29 06:18 作者: 充滿裝飾 時(shí)間: 2025-3-29 09:35
Mathematical Modeling of the Human Brainular algorithm or method. They have been written, debugged, and tested by the best experts in the field, as well as by a large supporting community of developers that contribute their time and expertise to maintain and improve them.作者: esculent 時(shí)間: 2025-3-29 12:52 作者: 休戰(zhàn) 時(shí)間: 2025-3-29 18:09 作者: 不給啤 時(shí)間: 2025-3-29 21:26
Pythonular algorithm or method. They have been written, debugged, and tested by the best experts in the field, as well as by a large supporting community of developers that contribute their time and expertise to maintain and improve them.作者: 名次后綴 時(shí)間: 2025-3-30 02:31 作者: Instinctive 時(shí)間: 2025-3-30 04:48 作者: concert 時(shí)間: 2025-3-30 08:42 作者: 桶去微染 時(shí)間: 2025-3-30 15:08 作者: PHAG 時(shí)間: 2025-3-30 20:30
Google Cloud Storage (GCS) 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).作者: 忙碌 時(shí)間: 2025-3-30 23:53 作者: 爭(zhēng)論 時(shí)間: 2025-3-31 03:52
JupyterLab Notebooksrelevant software packages for carrying out analytics and modeling tasks. It also makes available high-performance computing TPU and GPU processing capabilities at a single click. These VMs expose a JupyterLab notebook environment for analyzing data and designing machine learning models.作者: 純樸 時(shí)間: 2025-3-31 06:05
What Is Data Science?hematics, statistics, and computation. However, data science is now encapsulated into software packages and libraries, thus making them easily accessible and consumable by the software development and engineering communities. This is a major factor to the rise of intelligence capabilities now integr作者: 兇猛 時(shí)間: 2025-3-31 12:29 作者: 共同確定為確 時(shí)間: 2025-3-31 17:24 作者: Brochure 時(shí)間: 2025-3-31 17:50 作者: Thyroxine 時(shí)間: 2025-4-1 00:49 作者: 無法解釋 時(shí)間: 2025-4-1 05:18