Machine Learning - eBook (EN)

Jumpstart innovation with machine learning (NVidia)

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Introduction No longer limited to global technology enterprises and data science specialists, machine learning has entered the mainstream. Thanks to the cloud, the barriers to widespread use of machine learning are rapidly disappearing. The cloud brings together data, low- cost storage, security, and machine learning services along with high-performance, cost-effective CPU- and GPU-based compute instances, which are essential to machine learning success. The cloud also offers a pay- as-you-go cost model that further enables customers to control costs. More recently, complex deep learning models consisting of multiple layers of deep neural networks that mimic how a human brain functions necessitate even more powerful compute resources. Powerful GPUs coupled with CPUs, as well as the gigabytes or terabytes of storage advanced models require, must be managed in a secure, scalable, and cost-effective way to earn and keep customer trust. With the cloud, you can either choose fully managed services that automatically manage your infrastructure, so you don't need to worry about hardware and software maintenance, or you can opt for self-managed machine learning lifecycle management to benefit from the scale and security of the cloud while customizing infrastructure in a more hands-on way. Whatever you choose, with the cloud, you don't need to invest in all possible options upfront. Resources are available on demand and are always up to date and ready to provide you with purpose-built machine learning tools, storage, networking, and the latest infrastructure innovations. 2

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