Remove 2021 Remove Accessibility Remove Building Remove Deep Learning
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Build and deploy ML with ease Using Snowpark ML, Snowflake Notebooks, and Snowflake Feature Store

Snowflake

Snowflake has invested heavily in extending the Data Cloud to AI/ML workloads, starting in 2021 with the introduction of Snowpark , the set of libraries and runtimes in Snowflake that securely deploy and process Python and other popular programming languages. What’s Next?

Building 105
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The DataOps Vendor Landscape, 2021

DataKitchen

Download the 2021 DataOps Vendor Landscape here. DataOps is a hot topic in 2021. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Google Cloud Build . . Meta-Orchestration . Telm.ai — Telm.ai

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15 Deep Learning Projects Ideas for Beginners to Practice 2023

ProjectPro

As a beginner in the data industry, it can be overwhelming to step into AI and deep learning. After taking a deep learning course or two, you might find yourself getting stuck on how to proceed. Is it difficult to build deep learning models? Why build deep learning projects?

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Deep Learning vs Machine Learning -What's the Difference?

ProjectPro

“Machine Learning” and “Deep Learning” – are two of the most often confused and conflated terms that are used interchangeably in the AI world. However, there is one undeniable fact that both machine learning and deep learning are undergoing skyrocketing growth. respectively.

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Keras vs Tensorflow - Deep Learning Frameworks Battle Royale

ProjectPro

Machine Learning and Deep Learning have experienced unusual tours from bust to boom from the last decade. But when it comes to large data sets, determining insights from them through deep learning algorithms and mining them becomes tricky. Image Source: [link] Nowadays, Deep Learning is almost everywhere.

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Solved Music Genre Classification Project using Deep Learning

ProjectPro

Working with audio data has been a relatively less widespread and explored problem in machine learning. In most cases, benchmarks for the latest seminal work in deep learning are measured on text and image data performances. Amidst this, speech and audio, an equally important type of data, often gets overlooked.

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MLEnv: Standardizing ML at Pinterest Under One ML Engine to Accelerate Innovation

Pinterest Engineering

In 2021, ML was siloed at Pinterest with 10+ different ML frameworks relying on different deep learning frameworks, framework versions, and boilerplate logic to connect with our ML platform. It is very difficult for platform engineers to build good standardized tools that fit diverse ML stacks.