Towards AI

AUGUST 16, 2023

In fact, AI/ML graduate textbooks do not provide a clear and consistent description of the AI software engineering process. Therefore, I thought it would be helpful to give a complete description of the AI engineering process or AI Process, which is described in most AI/ML textbooks [5][6]. 85% or more of AI projects fail [1][2].

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

The machine learning (ML) model classifies new incoming customer requests as soon as they arrive and redirects them to predefined queues, which allows our dedicated client success agents to focus on the contents of the emails according to their skills and provide appropriate responses.

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The MLOps Blog

MAY 31, 2023

And eCommerce companies have a ton of use cases where ML can help. The problem is, with more ML models and systems in production, you need to set up more infrastructure to reliably manage everything. And because of that, many companies decide to centralize this effort in an internal ML platform. But how to build it?

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AWS Machine Learning Blog

JULY 31, 2023

Although machine learning (ML) can provide valuable insights, ML experts were needed to build customer churn prediction models until the introduction of Amazon SageMaker Canvas. Additional key topics Advanced metrics are not the only important tools available to you for evaluating and improving ML model performance.

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Pickl AI

AUGUST 28, 2024

From data preparation and model training to deployment and management, Vertex AI provides the tools and infrastructure needed to build intelligent applications. Overview of Vertex AI Vertex AI is a fully-managed, unified AI development platform that integrates all of Google Cloud’s existing ML offerings into a single environment.

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Iguazio

DECEMBER 14, 2023

Drawing from their extensive experience in the field, the authors share their strategies, methodologies, tools and best practices for designing and building a continuous, automated and scalable ML pipeline that delivers business value. The book is poised to address these exact challenges.

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Becoming Human

MAY 15, 2023

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

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Pickl AI

JULY 12, 2024

Here are a few of the key concepts that you should know: Machine Learning (ML) This is a type of AI that allows computers to learn without being explicitly programmed. Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data.

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Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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ODSC - Open Data Science

AUGUST 9, 2023

This is a straightforward and mostly clear-cut question — most of us can likely classify a dish as a dessert or not simply by reading its name, which makes it an excellent candidate for a simple ML model. The inferSchema parameter is set to True to infer the data types of the columns, and header is set to True to use the first row as headers.

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The MLOps Blog

OCTOBER 20, 2023

And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. When data science was sexy , notebooks weren’t a thing yet.

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