Dataconomy

JUNE 13, 2023

AI algorithms play a crucial role in decision intelligence. Rule-based systems, optimization techniques, or probabilistic frameworks are employed to guide decision-making based on the insights gained from data analysis and AI algorithms. How does decision intelligence work?

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Pickl AI

JANUARY 29, 2024

The collective strength of both forms the groundwork for AI and Data Science, propelling innovation. Markets for each field are booming, offering diverse job roles, especially in Machine Learning for Data Analytics. ML catalyses AI advancements, enabling systems to evolve and improve decision-making. billion by 2032.

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Pickl AI

SEPTEMBER 16, 2024

Applications Medical Diagnosis: Predicting disease outcomes based on patient data. Stock Market Predictions : Forecasting stock prices based on historical data. Support Vector Machines (SVM) Support Vector Machines are powerful supervised learning algorithms used for classification and regression tasks.

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How to Learn Machine Learning

JUNE 9, 2024

The thought of machine learning and AI will definitely pop into your mind when the conversation is about emerging technologies. Today, we see tools and systems with machine-learning capabilities in almost every industry. It is one of the best machine learning trends for 2024 that one should stay up-to-date with.

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IBM Journey to AI blog

JULY 6, 2023

What is machine learning? Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Machine learning can then “learn” from the data to create insights that improve performance or inform predictions.

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Data Science Blog

OCTOBER 20, 2024

Moreover, random forest models as well as support vector machines (SVMs) are also frequently applied. All those models are part of the Machine Learning & AI Toolkit for assessing MTA. Those models can capture the long-range dependencies among multiple touchpoints.

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Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. Python’s strength in AI development lies in its rich ecosystem of libraries.

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Pickl AI

SEPTEMBER 30, 2024

Common algorithms include decision trees, neural networks, and support vector machines. The more data available, the better the model can learn and make accurate predictions. Companies can leverage predictive analytics to forecast market trends, optimise pricing strategies, and identify potential risks.

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Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Is Deep Learning just another name for AI? Is all AI Deep Learning?

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Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

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Pickl AI

JULY 1, 2024

Random Forests By combining predictions from multiple decision trees, random forests improve accuracy and reduce overfitting. Support Vector Machines (SVMs) SVMs create a hyperplane to separate different data classes, helping predict future demand based on historical patterns.

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Pickl AI

NOVEMBER 18, 2024

Ethical considerations are crucial in developing fair Machine Learning solutions. Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed.

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ODSC - Open Data Science

JANUARY 7, 2025

Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly. Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way.

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Heartbeat

OCTOBER 23, 2023

Predictive Modeling and Risk Stratification: They also develop predictive models to forecast disease progression and patient outcomes and identify high-risk individuals for developing specific health conditions. Another notable application is predictive analytics in healthcare.

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Pickl AI

OCTOBER 15, 2024

In more complex cases, you may need to explore non-linear models like decision trees, support vector machines, or time series models. Here are some key applications: Healthcare: Used for predicting patient outcomes, analysing treatment effectiveness, and optimising resource allocation.

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