AWS Machine Learning Blog

JUNE 22, 2023

Light & Wonder teamed up with the Amazon ML Solutions Lab to use events data streamed from LnW Connect to enable machine learning (ML)-powered predictive maintenance for slot machines. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets.

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Pickl AI

JANUARY 29, 2024

2024 Tech breakdown: Understanding Data Science vs ML vs AI Quoting Eric Schmidt , the former CEO of Google, ‘There were 5 exabytes of information created between the dawn of civilisation through 2003, but that much information is now created every two days.’ billion in 2022 to a remarkable USD 484.17 billion by 2029.

Data Science 52

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Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

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Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

As part of its goal to help people live longer, healthier lives, Genomics England is interested in facilitating more accurate identification of cancer subtypes and severity, using machine learning (ML). We provide insights on interpretability, robustness, and best practices of architecting complex ML workflows on AWS with Amazon SageMaker.

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Pickl AI

NOVEMBER 28, 2024

Introduction Machine Learning ( ML ) is revolutionising industries, from healthcare and finance to retail and manufacturing. As businesses increasingly rely on ML to gain insights and improve decision-making, the demand for skilled professionals surges. billion in 2022 and is expected to grow to USD 505.42

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DrivenData Labs

JANUARY 22, 2025

Summary of modeling approach: There are two model architectures underlying the solution, each one implemented using two different gradient boosting on decision trees methods (Catboost and LightGBM) for a total of four models. Check out Christoph's full write-up and solution for the Final Prize Stage in the challenge winners repository.

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Mlearning.ai

MARCH 16, 2023

For instance, think of a scenario where the CMO of your company for the period of summer 2023 wants to use the exact same model that we’ve used during summer 2022. This is a business decision that we, as engineers, must pull it off. And by “same” we mean the same model in terms of parameters and the exact same training data.

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Heartbeat

SEPTEMBER 13, 2023

The " Decision Tree " is a popular example of the rule-based model that offers interpretable insights into how the model arrives at its decisions. Decision trees can be trained and visualized in rule-based explanations to reveal the underlying decision logic. Russell, C. & & Watcher, S.

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Ocean Protocol

MARCH 11, 2024

Transitioning to AI and machine learning (ML), participants developed models for precise weather prediction at KMIA. Andrey developed a machine-learning model and trained it to predict METAR data for the next hour, comparing different models ( linear regression, decision trees, and neural networks) and choosing the best based on performance.

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Pickl AI

SEPTEMBER 3, 2023

CAGR during 2022-2030. On the other hand, 48% use ML and AI for gaining insights into the prospects and customers. An ensemble of decision trees is trained on both normal and anomalous data. Further, it will provide a step-by-step guide on anomaly detection Machine Learning python.

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Mlearning.ai

APRIL 17, 2023

It is similar to the random forest in that it combines multiple decision trees to create a strong learner. It iteratively builds a sequence of decision trees, where each tree is trained to correct the errors made by the previous trees in the sequence.

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Mlearning.ai

FEBRUARY 6, 2023

There are plenty of techniques to help reduce overfitting in ML models. One such model could be Neural Prototype Trees [11], a model architecture that makes a decision tree off of “prototypes,” or interpretable representations of patterns in data. 2022) Shtetl-Optimized: The Blog of Scott Aaronson. [11] Nauta, R.v.

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Mlearning.ai

APRIL 13, 2023

Gaussian kernels are commonly used for classification problems that involve non-linear boundaries, such as decision trees or neural networks. Laplacian Kernels Laplacian kernels, also known as Laplacian of Gaussian (LoG) kernels, are used in decision trees or neural networks like image processing for edge detection.

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O'Reilly Media

FEBRUARY 20, 2024

Since its release in November 2022, almost everyone involved with technology has experimented with ChatGPT: students, faculty, and professionals in almost every discipline. Some models are inherently explainable—for example, simple decision trees. Whether the answer is honest may be another issue.)

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Dataconomy

SEPTEMBER 1, 2023

The time has come for us to treat ML and AI algorithms as more than simple trends. This technological journey of humanity, which started with the slow integration of IoT systems such as Alexa into our lives, has peaked in the last quarter of 2022 with the increase in the prevalence and use of ChatGPT and other LLM models.

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Iguazio

APRIL 24, 2024

Ever since the release of ChatGPT in November 2022, organizations have been trying to find new and innovative ways to leverage gen AI to drive organizational growth. LLMs vs. Classical ML Models: Strengths and Capabilities LLMs and ML models each have their distinct strengths, which can be applied to different kinds of tasks and objectives.

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Dataconomy

APRIL 4, 2024

From deterministic software to AI Earlier examples of “thinking machines” included cybernetics (feedback loops like autopilots) and expert systems (decision trees for doctors). When the result is unexpected, that’s called a bug. But these were still predictable and understandable. They just followed a lot of rules. and ChatGPT.

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