IBM Journey to AI blog

SEPTEMBER 20, 2023

These massive amounts of data that exist in every business are waiting to be unleashed to drive insights. Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. What are large language models?

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Large Language Models DevOps Data Science AI Modeling 238

AWS Machine Learning Blog

MAY 15, 2023

Algorithm Selection Amazon Forecast has six built-in algorithms ( ARIMA , ETS , NPTS , Prophet , DeepAR+ , CNN-QR ), which are clustered into two groups: statististical and deep/neural network. Deep/neural network algorithms also perform very well on sparse data set and in cold-start (new item introduction) scenarios.

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IBM Journey to AI blog

OCTOBER 20, 2023

Get to know IBM watsonX IBM watsonx is an AI and data platform with a set of AI assistants designed to help you scale and accelerate the impact of AI with trusted data across your business. This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

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IBM Journey to AI blog

JUNE 23, 2023

The introduction of ChatGPT capabilities has generated a lot of interest in generative AI foundation models (these are pre-trained on unlabeled datasets and leverage self-supervised learning with the help of Large Language Models using a neural network ).

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AWS Machine Learning Blog

DECEMBER 7, 2023

Six algorithms available in Forecast were tested: Convolutional Neural Network – Quantile Regression (CNN-QR), DeepAR+ , Prophet , Non-Parametric Time Series (NPTS), Autoregressive Integrated Moving Average (ARIMA), and Exponential Smoothing (ETS). He loves combining open-source projects with cloud services.

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DataRobot Blog

MARCH 16, 2023

Why model-driven AI falls short of delivering value Teams that just focus model performance using model-centric and data-centric ML risk missing the big picture business context. This narrow focus can lead to accurate and true insights that are not really useful, leaving business stakeholders feeling frustrated.

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ODSC - Open Data Science

SEPTEMBER 17, 2024

LightGBM’s ability to handle large-scale data with lightning speed makes it a valuable tool for engineers working with high-dimensional data. It’s particularly popular for image classification and convolutional neural networks CNNs. Caffe Caffe is a deep learning framework focused on speed, modularity, and expression.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

We used a convolutional neural network (CNN) architecture with ResNet152 for image classification. He has worked on building enterprise-grade applications, building data platforms in multiple organizations and reporting platforms to streamline decisions backed by data.

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The MLOps Blog

MAY 31, 2023

You may also like Building a Machine Learning Platform [Definitive Guide] Consideration for data platform Setting up the Data Platform in the right way is key to the success of an ML Platform. In the following sections, we will discuss best practices while setting up a Data Platform for Retail.

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The MLOps Blog

JANUARY 26, 2024

Keeping track of how exactly the incoming data (the feature pipeline’s input) has to be transformed and ensuring that each model receives the features precisely how it saw them during training is one of the hardest parts of architecting ML systems. This is where feature stores come in. What is a feature store?

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ODSC - Open Data Science

JULY 20, 2023

This open-source startup that specializes in neural networks has made a name for itself building a platform that allows organizations to train large language models. Databricks Buying MosaicML In an announcement late last month, Databricks said that they would pay $1.3 billion to acquire MosaicML.

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ODSC - Open Data Science

MARCH 8, 2024

Definition The Vision Transformer (ViT) emerged as an alternative to Convolutional Neural Networks (CNNs). By teaching the model to attend to relevant input data while disregarding irrelevant portions, ViT enhances its ability to tackle tasks effectively. For example, we can use a Vision Transformer for this purpose.

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Pickl AI

OCTOBER 25, 2023

It involves the use of algorithms, neural networks , and Machine Learning to enable machines to perform tasks that typically require human intelligence. The quality of input data greatly influences the effectiveness of AI models. Data Analysis Big Data analytics provides AI with the fuel it needs to function.

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Marktechpost

JULY 17, 2023

It is impossible to completely substitute accurate data because precise, accurate data are still needed to generate practical synthetic examples of the information. How Important Is Synthetic Data? To train neural networks, developers require vast, meticulously annotated datasets.

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Marktechpost

NOVEMBER 1, 2024

PyTorch, an open-source framework, is widely used in both commercial and academic applications, especially when neural networks are needed. It offers a user-friendly starting point for anyone who wants to examine their data and predict results. Deep learning practitioners choose it because of its large community and libraries.

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Bugra Akyildiz

FEBRUARY 24, 2024

Streaming data platforms: Apache Kafka and Apache Flink enable real-time ingestion and processing of user actions, clickstream data, and product catalogs, feeding fresh data to the models. Libraries DeepSparse is a CPU inference runtime that takes advantage of sparsity to accelerate neural network inference.

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