Smart Data Collective

SEPTEMBER 16, 2020

These statistical models are growing as a result of the wide swaths of available current data as well as the advent of capable artificial intelligence and machine learning. Data Sourcing. Deep Learning, Machine Learning, and Automation.

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Pickl AI

NOVEMBER 18, 2024

Summary: The blog provides a comprehensive overview of Machine Learning Models, emphasising their significance in modern technology. It covers types of Machine Learning, key concepts, and essential steps for building effective models. The global Machine Learning market was valued at USD 35.80

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Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field. billion by 2031, growing at a CAGR of 34.20%.

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Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced.

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AWS Machine Learning Blog

OCTOBER 8, 2024

SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment. Data preparation The foundation of any machine learning project is data preparation.

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Towards AI

JULY 19, 2023

Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. Data Preparation Photo by Bonnie Kittle […]

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Ocean Protocol

NOVEMBER 28, 2024

Introduction The Formula 1 Prediction Challenge: 2024 Mexican Grand Prix brought together data scientists to tackle one of the most dynamic aspects of racing — pit stop strategies. With every second on the track critical, the challenge showcased how data can shape decisions that define race outcomes.

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Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.

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Pickl AI

JULY 1, 2024

Data Preparation for Demand Forecasting High-quality data is the cornerstone of effective demand forecasting. Just like building a house requires a strong foundation, building a reliable forecast requires clean and well-organized data. For example, combine daily sales data to create weekly or monthly sales figures.

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AWS Machine Learning Blog

JUNE 22, 2023

Utilizing data streamed through LnW Connect, L&W aims to create better gaming experience for their end-users as well as bring more value to their casino customers. With predictive maintenance, L&W can get advanced warning of machine breakdowns and proactively dispatch a service team to inspect the issue.

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Pickl AI

DECEMBER 12, 2024

Summary: XGBoost is a highly efficient and scalable Machine Learning algorithm. It combines gradient boosting with features like regularisation, parallel processing, and missing data handling. This blog explores XGBoosts unique characteristics, practical applications, and how it revolutionises Machine Learning workflows.

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phData

AUGUST 24, 2023

Credit scoring and decisioning models have been used by financial institutions for many years to predict the risk associated with lending to individuals or entities. However, these models are evolving, with machine learning now playing an essential role in refining and improving the accuracy and efficiency of credit scoring and decisioning.

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Pickl AI

FEBRUARY 4, 2024

Alteryx’s Capabilities Data Blending: Effortlessly combine data from multiple sources. Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data.

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ODSC - Open Data Science

OCTOBER 7, 2024

In today’s landscape, AI is becoming a major focus in developing and deploying machine learning models. It isn’t just about writing code or creating algorithms — it requires robust pipelines that handle data, model training, deployment, and maintenance. Model Training: Running computations to learn from the 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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Pickl AI

OCTOBER 3, 2024

Summary: Predictive analytics utilizes historical data, statistical algorithms, and Machine Learning techniques to forecast future outcomes. This blog explores the essential steps involved in analytics, including data collection, model building, and deployment. What is Predictive Analytics?

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DagsHub

APRIL 21, 2024

Source: [link] Similarly, while building any machine learning-based product or service, training and evaluating the model on a few real-world samples does not necessarily mean the end of your responsibilities. MLOps tools play a pivotal role in every stage of the machine learning lifecycle. What is MLOps?

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Pickl AI

NOVEMBER 5, 2024

Artificial Intelligence, on the other hand, refers to the simulation of human intelligence in machines programmed to think and learn like humans. AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision.

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PyImageSearch

OCTOBER 21, 2024

By leveraging machine learning techniques, businesses can significantly reduce downtime and maintenance costs, ensuring smoother and more efficient operations. For instance, if a machine usually operates within a certain temperature range, a sudden spike in temperature could be an anomaly, signaling a problem.

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Pickl AI

NOVEMBER 12, 2024

Simulink provides blocks specifically designed for AI functions, allowing you to incorporate Machine Learning or deep learning models seamlessly. This involves: Data Preparation : Collect and preprocess data to ensure it is suitable for training your model.

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Pickl AI

MAY 30, 2024

You will collect and clean data from multiple sources, ensuring it is suitable for analysis. You will perform Exploratory Data Analysis to uncover patterns and insights hidden within the data. Choosing Appropriate Algorithms Choosing the correct algorithm depends on the problem and data.

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The MLOps Blog

DECEMBER 19, 2022

Classification is one of the most widely applied areas in Machine Learning. As Data Scientists, we all have worked on an ML classification model. A Multiclass Classification is a class of problems where a given data point is classified into one of the classes from a given list.

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Data Science Dojo

AUGUST 30, 2023

Hypothesis testing, correlation, and regression analysis, and distribution analysis are some of the essential statistical tools that data scientists use. Machine learning algorithms Machine learning forms the core of Applied Data Science.

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Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. As industries increasingly rely on data-driven insights, ethical considerations regarding data privacy and bias mitigation will become paramount.

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Dataconomy

MARCH 28, 2025

Machine learning algorithms represent a transformative leap in technology, fundamentally changing how data is analyzed and utilized across various industries. What are machine learning algorithms? Regression: Focuses on predicting continuous values, such as forecasting sales or estimating property prices.

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Dataconomy

MARCH 18, 2025

CatBoost is quickly becoming a go-to algorithm in the machine learning landscape, particularly for its innovative approach to handling categorical data. CatBoost stands out for its design aimed at efficiently processing categorical data.

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How to Learn Machine Learning

MARCH 25, 2025

Understanding Supervised vs Unsupervised Learning: A Comparative Overview Introduction Hello dear readers, hope you’re doing just fine! (Or Or even better than that) Machine learning has transformed the way businesses operate by automating processes, analyzing data patterns, and improving decision-making.

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