cloud-covered 
Analytics Vidhya
OCTOBER 14, 2022
Introduction The distribution of computer services through the internet is known as cloud computing. Businesses can adopt the cloud computing paradigm, where they can rent IT equipment and services instead of purchasing and operating their data centers. These services cover everything from basic infrastructures […].
Analytics Vidhya
NOVEMBER 7, 2022
Introduction Cloud security is the practice of protecting data and information that is stored on or accessed through a cloud computing service. It is a broad term that covers a range of security concerns, from the physical infrastructure of the cloud to the […].
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Analytics Vidhya
FEBRUARY 21, 2023
Introduction Cloud engineers are responsible for building and monitoring cloud-based systems. They must deeply understand cloud technology, platform architecture, data science, and system integration. Are you preparing for a cloud engineer interview? Do you want to stand out and land your dream job? Look no further!
Marktechpost
MAY 30, 2024
Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. It covers how to develop NLP projects using neural networks with Vertex AI and TensorFlow.
Speaker: Ryan Bryers, SVP of Global Engineering
In a rapidly evolving industry, the shift from traditional on-premise systems to cloud-based solutions has become crucial for retail success. While many businesses still rely on store-level infrastructure, it's time to embrace the unlimited potential of the cloud!
Marktechpost
APRIL 7, 2024
Machine Learning Design Patterns “Machine Learning Design Patterns” covers the most common problems in machine learning and its solutions. Machine Learning Engineering This book covers the different machine learning engineering best practices and design patterns.
Marktechpost
MAY 14, 2024
Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It covers TensorFlow 2.x The book also covers building and deploying various algorithms like CNNs, transformers, GANs, etc.
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