Smart Data Collective

JUNE 7, 2019

Machine learning is playing a very important role in improving the functionality of task management applications. Appreciating the Machine Learning Technology Behind Modern Task Management Software. Both of these types of learning are used by machine learning algorithms in modern task management applications.

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Dataconomy

OCTOBER 5, 2023

Artificial intelligence, one of the most talked about topics in today’s technology world, has played a huge role in bringing many things into our lives, especially in the last five years. But does that mean artificial intelligence is perfect? The next critical step is model selection.

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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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How to Learn Machine Learning

JANUARY 21, 2023

Check out our best 7 Artificial Intelligence Project Ideas to enhance your practice and level up your skill! As Artificial Intelligence (AI) continues to become more and more prevalent in our daily lives, it’s no surprise that more and more people are eager to learn how to work with the technology.

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Mlearning.ai

MARCH 13, 2023

Photo by Andy Kelly on Unsplash Choosing a machine learning (ML) or deep learning (DL) algorithm for application is one of the major issues for artificial intelligence (AI) engineers and also data scientists. Explore algorithms: Research and explore different algorithms that are desired for your problem.

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Dataconomy

JUNE 13, 2023

Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights. Think of decision intelligence as a synergy between the human mind and cutting-edge algorithms. What is decision intelligence?

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Dataconomy

FEBRUARY 24, 2023

The term “artificial intelligence” (AI) describes machines’ ability to mimic human intelligence. Artificial Intelligence (AI) can be used in various ways to solve complex problems and automate tasks that were previously done manually. Yes, even lawyers, doctors, and more. What is AI?

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Becoming Human

MARCH 16, 2023

How AI is applied Artificial Intelligence covers various technologies and approaches that involve using sophisticated computational methods to mimic elements of human intelligence such as visual perception, speech recognition, decision-making, and language understanding. A few AI technologies are empowering drug design.

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ODSC - Open Data Science

FEBRUARY 13, 2023

The field of data science changes constantly, and some frameworks, tools, and algorithms just can’t get the job done anymore. How Deep Neural Networks Work and How We Put Them to Work at Facebook Deep learning is the technology driving today’s artificial intelligence boom.

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Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

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Mlearning.ai

APRIL 6, 2023

However, with a wide range of algorithms available, it can be challenging to decide which one to use for a particular dataset. In this article, we will discuss some of the factors to consider while selecting a classification & Regression machine learning algorithm based on the characteristics of the data.

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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Towards AI

JULY 20, 2023

This ongoing process straddles the intersection between evidence-based medicine, data science, and artificial intelligence (AI). As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process.

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Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Markets for each field are booming, offering diverse job roles, especially in Machine Learning for Data Analytics.

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Mlearning.ai

FEBRUARY 17, 2023

A complete explanation of the most widely practical and efficient field, that nowadays has an impact on every industry Photo by Thomas T on Unsplash Machine learning has become one of the most rapidly evolving and popular fields of technology in recent years. Great example of this tecnique is K-means clustering algorithm.

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Towards AI

APRIL 11, 2023

Classification In Classification, we use an ML Algorithm to classify the digit based on its features. The algorithm can be trained on a dataset of labeled digit images, which allows it to learn to recognize the patterns in the images. Artificial Neural Networks (ANNs) are machine learning models that can be used for HDR.

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Dataconomy

AUGUST 9, 2023

This is where the power of machine learning (ML) comes into play. Machine learning algorithms, with their ability to recognize patterns, anomalies, and trends within vast datasets, are revolutionizing network traffic analysis by providing more accurate insights, faster response times, and enhanced security measures.

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Heartbeat

MARCH 8, 2023

To extract themes from a corpus of text data and then use these themes as features in text classification algorithms, topic modeling can be used in text classification. The e1071 package provides a suite of statistical classification functions, including support vector machines (SVMs), which are commonly used for spam detection.

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How to Learn Machine Learning

DECEMBER 15, 2024

Covering a comprehensive range of topics, the course provides a deep dive into the fundamental principles and practical applications of machine learning algorithms. This professional certificate provides a holistic approach to machine learning, combining theoretical knowledge with practical skills.

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Flipboard

JULY 31, 2023

Brief Background of Machine Learning Did you know that machine learning is a part of artificial intelligence that enables computers to learn from data without explicit programming using statistical techniques? Importance and Role of Datasets in Machine Learning Data is king. Many call this software 2.0.

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Pickl AI

JULY 14, 2023

Artificial Intelligence has been able to gain immense momentum today and is transforming every industry in the world. Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications.

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Pickl AI

FEBRUARY 7, 2025

Introduction In todays world of AI, both Machine Learning (ML) and Deep Learning (DL) are transforming industries, yet many confuse the two. While both are subsets of Artificial Intelligence, they differ significantly regarding techniques and applications. What is Machine Learning?

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].” It detects corners.

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Pickl AI

SEPTEMBER 10, 2024

Introduction The Perceptron is one of the foundational concepts in Artificial Intelligence and Machine Learning. The Perceptron learning algorithm adjusts the weights and bias based on the errors made during predictions. However, if the data is not linearly separable, the Perceptron may fail to converge.

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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.

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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

Algorithmic Attribution using binary Classifier and (causal) Machine Learning While customer journey data often suffices for evaluating channel contributions and strategy formulation, it may not always be comprehensive enough. Moreover, random forest models as well as support vector machines (SVMs) are also frequently applied.

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How to Learn Machine Learning

JUNE 9, 2024

In this article, we will explore the top 5 machine learning trends for 2024 that will completely change how we live and perform tasks. Machine Learning and Its Importance Machine learning is a subset of artificial intelligence. It dramatically shortens computing times for complex algorithms.

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PyImageSearch

NOVEMBER 13, 2023

One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,

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Heartbeat

OCTOBER 25, 2023

Bioinformatics algorithms and tools have played a crucial role in analyzing NGS data, enabling researchers to study genetic variations, gene expression patterns, and epigenetic modifications on a large scale. While bioinformatics has made remarkable strides in advancing biological research, it faces several challenges that must be overcome.

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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. In the same way, ML algorithms can be trained on large datasets to learn patterns and make predictions based on that data.

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Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Machine Learning?

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Pickl AI

SEPTEMBER 30, 2024

What is Machine Learning? ML is a subset of Artificial Intelligence that enables computers to learn from data without explicit programming. Key concepts in ML are: Algorithms : Algorithms are the mathematical instructions that guide the learning process. Data : Data serves as the foundation for ML.

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