Google Research AI blog

FEBRUARY 7, 2023

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. Below, we highlight a panoply of works that demonstrate Google Research’s efforts in developing new algorithms to address the above challenges.

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Pickl AI

MAY 10, 2023

Machine Learning is a subset of Artificial Intelligence and Computer Science that makes use of data and algorithms to imitate human learning and improving accuracy. Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification. What is Classification?

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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

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Data Science Dojo

AUGUST 19, 2024

Business Benefits: Organizations are recognizing the value of AI and data science in improving decision-making, enhancing customer experiences, and gaining a competitive edge An AI research scientist acts as a visionary, bridging the gap between human intelligence and machine capabilities. Privacy: Protecting user privacy and data security.

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Pickl AI

AUGUST 6, 2023

Regression Machine Learning algorithms is a statistical method that you can use to model the relationship between dependent variables and one or more independent variables. Effectively, regression algorithms helps in determining the best-fit line. The algorithm is simple to interpret and can capture complex relationships in the data.

Machine Learning 52

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Dataconomy

OCTOBER 5, 2023

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. Over time, the algorithm improves its accuracy and can make better predictions on new, unseen data.

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Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. 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.

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ODSC - Open Data Science

NOVEMBER 13, 2023

Predictive analytics is rapidly becoming indispensable in data-driven decision-making, especially grant funding. It uses statistical algorithms and machine learning techniques to analyze historical data and predict future outcomes. Interested in attending an ODSC event? Learn more about our upcoming events here.

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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. It also highlights diverse applications across industries such as healthcare, retail, finance, and marketing for enhanced decision-making. What is Predictive Analytics?

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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 91

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 91

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

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ODSC - Open Data Science

NOVEMBER 30, 2023

Explainable AI (XAI) refers to AI that explains how, where, and why it produces decisions. XAI coincides with white-box models, which detail the results the algorithms have. It uses data mining techniques like decision trees and rule-based systems to generate correct responses. Interested in attending an ODSC event?

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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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ODSC - Open Data Science

SEPTEMBER 18, 2023

Classic Machine Learning in NLP The following section explores how traditional machine learning algorithms can be applied to NLP tasks. Interested in attending an ODSC event? Learn more about our upcoming events here. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

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Dataconomy

MAY 25, 2023

By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions. This enables them to extract valuable insights, identify patterns, and make informed decisions in real-time.

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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. Popular clustering algorithms include k-means and hierarchical clustering.

Decision Trees 52

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Dataconomy

OCTOBER 11, 2024

Predictive AI is designed to forecast future events based on historical data. This makes it more like a sophisticated crystal ball—but with data, algorithms, and statistical rigor behind it. Predictive AI is often used in scenarios that require informed decision-making. ” or “Which customers are most likely to churn?”

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AI AI Decision Trees Artificial Intelligence 121

Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. In both cases, algorithms are trained to generate predictions or judgments based on data inputs. Machine learning algorithms can make predictions or classifications based on input data. What is Machine Learning?

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Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. 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.

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Pickl AI

SEPTEMBER 3, 2023

Observations that deviate from the majority of the data are known as anomalies and might take the shape of occurrences, trends, or events that differ from customary or expected behaviour. Finding anomalous occurrences that might point to intriguing or potentially significant events is the aim of anomaly detection.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Mlearning.ai

APRIL 4, 2023

Instead of traditional segmentation based on hard business metrics, financial institutions can group customers into smaller micro-segments using fine-tuned ML algorithms. Conclusion In short, ML algorithms enable lenders to get meaningful insights on the expected losses in case of default, based on historical and current information.

Machine Learning 52

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ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn A machine learning powerhouse, Scikit-learn provides a vast collection of algorithms and tools, making it a go-to library for many data scientists. Interested in attending an ODSC event? Learn more about our upcoming events here. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. Decision trees are more prone to overfitting.

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Pickl AI

AUGUST 23, 2023

By extracting insights from these datasets, professionals can make more informed investment decisions, reducing the risk associated with emotional biases. Through sophisticated algorithms and Machine Learning models , data scientists can predict stock price movements with a degree of accuracy that was previously unthinkable.

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Ocean Protocol

MARCH 11, 2024

Through this process, they gained valuable insights into Miami’s meteorological landscape, including seasonal variations and significant weather events impacting KMIA operations. Points will now be awarded to the top 10 finishers in each event, with 100 championship points up for grabs.

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Mlearning.ai

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

Decision Trees 52

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Pickl AI

JULY 23, 2023

It requires sophisticated tools and algorithms to derive meaningful patterns and trends from the sheer magnitude of data. Real-time data feeds and algorithmic trading strategies have transformed the dynamics of financial markets. It involves investigating the root causes behind specific outcomes or trends observed in the data.

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Pickl AI

OCTOBER 18, 2023

6 Elements of Data Quality Accuracy Data accuracy measures how well the data reflects the real-world entities or events it represents. Algorithms for Data Quality Enhancement Choosing the right algorithms and queries is imperative for companies dealing with extensive datasets. It should closely match the true values or facts.

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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.

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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.

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Heartbeat

APRIL 17, 2023

Photo by Shahadat Rahman on Unsplash Introduction Machine learning (ML) focuses on developing algorithms and models that can learn from data and make predictions or decisions. Human brains are capable of processing vast amounts of information from the environment and making complex decisions based on that information.

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Smart Data Collective

JUNE 26, 2019

Three years later, the code was released as hey solution for machine learning algorithms in conjunction with Google and several other major companies. Scikit-learn is a library that contains several implementations of machine learning algorithms. Decision tree pruning and induction. Decision boundary learning with SVMs.

Machine Learning 77

Machine Learning Machine Learning Python Decision Trees 77

Pickl AI

AUGUST 9, 2024

Students should understand the concepts of event-driven architecture and stream processing. Machine Learning Algorithms Basic understanding of Machine Learning concepts and algorithm s, including supervised and unsupervised learning techniques. Finance Applications in fraud detection, risk assessment, and algorithmic trading.

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Pickl AI

JULY 14, 2023

Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Heartbeat

SEPTEMBER 13, 2023

Algorithmic Accountability: Explainability ensures accountability in machine learning and AI systems. It allows developers, auditors, and regulators to examine the decision-making processes of the models, identify potential biases or errors, and assess their compliance with ethical guidelines and legal requirements. O'Sullivan, C.

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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. Hybrid machine learning techniques can help with effective heart disease prediction by combining the strengths of different machine learning algorithms and utilizing them in a way that maximizes their predictive power.

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Dataconomy

FEBRUARY 24, 2023

Choose the appropriate algorithm: Select the AI algorithm that best suits the problem you want to solve. Several algorithms are available, including decision trees, neural networks, and support vector machines. This involves feeding the algorithm with data and tweaking it to improve its accuracy.

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