Data Science Dojo

AUGUST 27, 2024

They might find that it’s because of a popular deal or event on Tuesdays. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Imagine you’re trying to figure out why your favorite coffee shop is always busy on Tuesdays.

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ODSC - Open Data Science

MAY 31, 2023

Apache Kafka is an event streaming platform that collects, stores, and processes streams of data (events) in real-time and in an elastic, scalable, and fault-tolerant manner. Consumers read the events and process the data in real-time. The TensorFlow instance acts as a Kafka consumer to load new events into its memory.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Smart Data Collective

SEPTEMBER 16, 2020

Fundamental to any aspect of data science, it’s difficult to develop accurate predictions or craft a decision tree if you’re garnering insights from inadequate data sources. The applications of predictive analytics are extensive and often require four key components to maintain effectiveness. Data Sourcing.

Predictive Analytics 139

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IBM Journey to AI blog

AUGUST 9, 2024

It extracts insights from historical data to make accurate predictions about the most likely upcoming event, result or trend. Output While both AI systems employ an element of prediction to produce their outputs, generative AI creates novel content whereas predictive AI forecasts future events and outcomes.

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AI AI Decision Trees Algorithm 120

AWS Machine Learning Blog

JUNE 22, 2023

Over 500 machine events are monitored in near-real time to give a full picture of machine conditions and their operating environments. 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.

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Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. log2P(xi) measures the information content of each event in bits.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Clustering 52

ODSC - Open Data Science

NOVEMBER 30, 2023

It uses data mining techniques like decision trees and rule-based systems to generate correct responses. Interested in attending an ODSC event? Learn more about our upcoming events here. Other AI models offer numerous benefits, but the healthcare sector and its patients expect more accountability and accuracy.

AI 94

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Pickl AI

MAY 10, 2023

In case you need to determine the likelihood of an event occurring, the application of sigmoid function is important. Decision Trees Decision Trees are non-linear model unlike the logistic regression which is a linear model. Consequently, each brand of the decision tree will yield a distinct result.

Clustering 52

Clustering Decision Trees Machine Learning Machine Learning 52

Ocean Protocol

NOVEMBER 28, 2024

Participants used historical data from past Mexican Grand Prix events and insights from the 2024 F1 season to create machine-learning models capable of predicting key race elements. With every second on the track critical, the challenge showcased how data can shape decisions that define race outcomes.

Cross Validation 85

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Victor Zhou

MARCH 29, 2019

Decision Trees ? Training a decision tree consists of iteratively splitting the current data into two branches. Event Probability Pick Blue, Classify Blue ✓ 25% Pick Blue, Classify Green ❌ 25% Pick Green, Classify Blue ❌ 25% Pick Green, Classify Green ✓ 25% We only classify it incorrectly in 2 of the events above.

Decision Trees 52

Decision Trees 52

Dataconomy

OCTOBER 11, 2024

Predictive AI is designed to forecast future events based on historical data. Models like regression analysis, decision trees, and neural networks are often employed to predict outcomes. Generative AI, as the name suggests, focuses on creation What is predictive AI?

AI 121

AI AI Decision Trees Artificial Intelligence 121

ODSC - Open Data Science

NOVEMBER 13, 2023

Model Selection Among the commonly used types are decision trees and regression models , each with advantages depending on the problem you’re trying to solve. Decision trees break down complex decisions into more straightforward choices, represented by nodes on a tree-like graph.

Predictive Analytics 52

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Smart Data Collective

JUNE 26, 2019

Decision tree pruning and induction. Decision boundary learning with SVMs. events event_1,event_2, event_label 1,2,3 11.1,1221,11341 1322,1422,320 330,222,121. There are numerous reasons that scikit-learn is one of the preferred libraries for developing machine learning solutions. Advanced probability modeling.

Machine Learning 90

Machine Learning Machine Learning Python Decision Trees 90

Dataconomy

OCTOBER 5, 2023

Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. As such, it’s difficult to rely on software to accurately forecast where and when an event is set to occur. With the model selected, the initialization of parameters takes place.

AI 136

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Pickl AI

SEPTEMBER 7, 2023

Gradient Boosting Iteratively builds weak learners, usually decision trees, by focusing on the residuals of the previous iteration’s predictions. Build a weak learner, usually a shallow decision tree, to understand and capture the patterns in the residuals. Weak Learner Creation: Address model shortcomings.

Algorithm 52

Algorithm Decision Trees Machine Learning Machine Learning 52

Pickl AI

JULY 1, 2024

Decision Trees These tree-like structures categorize data and predict demand based on a series of sequential decisions. Random Forests By combining predictions from multiple decision trees, random forests improve accuracy and reduce overfitting. Ensemble Learning Combine multiple forecasting models (e.g.,

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Mlearning.ai

FEBRUARY 10, 2024

These mathematical domains serve as the crucial framework for comprehending patterns in data, allowing us to make highly accurate forecasts about future events. It serves as a fundamental principle in probability theory, illustrating how the likelihood of an event or hypothesis evolves as additional information is acquired.

Algorithm 52

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Data Science Dojo

AUGUST 16, 2023

Here are some of the key events in the history of transformers in neural networks: 1990: Jürgen Schmidhuber proposes the first transformer model, the “fast weight controller” 2017: Vaswani et al. It is now the go-to approach for many NLP tasks, and it is constantly being improved.

Natural Language Processing 195

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Data Science Dojo

AUGUST 16, 2023

Here are some of the key events in the history of transformers in neural networks: 1990: Jürgen Schmidhuber proposes the first transformer model, the “fast weight controller” 2017: Vaswani et al. It is now the go-to approach for many NLP tasks, and it is constantly being improved.

Natural Language Processing 195

Natural Language Processing Decision Trees Deep Learning Deep Learning 195

Heartbeat

OCTOBER 31, 2023

Before continuing, revisit the lesson on decision trees if you need help understanding what they are. We can compare the performance of the Bagging Classifier and a single Decision Tree Classifier now that we know the baseline accuracy for the test dataset. Bagging is a development of this idea.

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ODSC - Open Data Science

MARCH 29, 2024

You didn’t mention to them that the scorecard you built uses decision trees to strategically bin the variables in the model, you calculated the weight of evidence values for each of these bins and then inputted all of that into a logistic regression model with a high model performance. Interested in attending an ODSC event?

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

AUGUST 6, 2023

Decision Tree Regression: Decision tree regression is a non-parametric Machine Learning technique used for predicting continuous values. It constructs a tree-like structure by recursively splitting the data based on feature values, creating branches and leaf nodes. It is commonly used in medical research.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Supervised Learning 52

ODSC - Open Data Science

SEPTEMBER 18, 2023

In this introduction to NLP course, you’ll learn about algorithms such as Naive Bayes, SVMs, and decision trees and understand how to use them for text classification, sentiment analysis, topic modeling, and more. Interested in attending an ODSC event? Learn more about our upcoming events here.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

JUNE 5, 2024

And most machine learning tools will automatically generate summaries of complex data, making it easier for executives and other decision-makers to understand reports without needing to review the raw data themselves. Predictive analytics.

Analytics 94

Analytics Analytics AI AI 94

Pickl AI

DECEMBER 12, 2024

Introduction Boosting is a powerful Machine Learning ensemble technique that combines multiple weak learners, typically decision trees, to form a strong predictive model. Lets explore the mathematical foundation, unique enhancements, and tree-pruning strategies that make XGBoost a standout algorithm. Lower values (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

OCTOBER 15, 2024

They identify patterns in existing data and use them to predict unknown events. Techniques like linear regression, time series analysis, and decision trees are examples of predictive models. In more complex cases, you may need to explore non-linear models like decision trees, support vector machines, or time series models.

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AWS Machine Learning Blog

MAY 8, 2024

This meticulous approach allows Dialog Axiata to gain valuable insights into customer behavior, enabling them to predict potential churn events with remarkable accuracy. million subscribers, which amounts to 57% of the Sri Lankan mobile market. The base model, powered by CatBoost, provides a solid foundation for churn prediction.

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ML ML AWS AI 119

Cambridge Intelligence

FEBRUARY 20, 2024

FREE: Managing fraud The ultimate guide to fraud detection, investigation and prevention using data visualization GET YOUR FREE GUIDE The role of new & existing technology For many years, credit card companies have relied on analytics, algorithms and decision trees to power their fraud strategy.

AI 59

AI AI Machine Learning Machine Learning 59

Pickl AI

SEPTEMBER 12, 2024

Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Joint Probability: The probability of two events co-occurring, often used in Bayesian statistics and probability theory.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. But what is an anomaly and why is detecting it important?

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Mlearning.ai

APRIL 4, 2023

Precise credit risk assessments are made possible thanks to improved ML models (for instance, XGBoost, Light GBM, SVMs, Decision Trees and advanced Deep Learning algorithms). (A A Medium writer even built a credit risk model using some of the above-mentioned models — read here.) BECOME a WRITER at MLearning.ai

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Dataconomy

MAY 25, 2023

Real-time decision-making With AI, IoT devices can make decisions in real-time based on the data they collect and analyze. This enables them to respond quickly to changing conditions or events. Unsupervised learning Unsupervised learning involves training machine learning models with unlabeled datasets.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

ODSC - Open Data Science

JANUARY 5, 2024

Interested in attending an ODSC event? Learn more about our upcoming events here. Scikit-learn is also open-source, which makes it a popular choice for both academic and commercial use. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Heartbeat

JULY 18, 2023

NLP with RandomForest Random Forest is a widely used machine learning technique that employs an ensemble of decision trees to make predictions. This method involves creating multiple decision trees from a random selection of features and training each tree on a random sample of the data.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning ML 52

ODSC - Open Data Science

OCTOBER 23, 2024

Many of these speakers are familiar faces at past ODSC events or are regular contributors to major AI and tech conferences. Matt Harrison’s Talk: Machine Learning with XGBoost XGBoost is one of the most widely used machine learning algorithms today, known for its speed and accuracy in decision tree-based models.

Data Science 40

Data Science Data Scientist AI AI 40

Mlearning.ai

MAY 23, 2023

Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. character) is underlined or not.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

OCTOBER 3, 2024

Predictive analytics refers to the use of statistical algorithms and Machine Learning techniques to analyse historical data and predict future events or outcomes. Decision Trees : Help visualise decisions and their possible consequences. What is Predictive Analytics? How Does Analytics Benefit Businesses?

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