Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. 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.

Internet of Things 160

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Snorkel AI

OCTOBER 31, 2023

The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. We are excited to present the following papers and presentations during this year’s event. Characterizing the Impacts of Semi-supervised Learning for Weak Supervision Li et al.

Supervised Learning 59

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ODSC - Open Data Science

SEPTEMBER 12, 2024

Week 1: Introduction to AI Dive deep into the basics of AI and machine learning during week 1. Explore the different types of AI and then fundamental concepts like algorithms, models, and features. Week 2: Machine Learning Data Prep with Python Learn the fundamentals of one of the most powerful tools for data prep during week 2.

Machine Learning 40

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How to Learn Machine Learning

SEPTEMBER 6, 2024

AI for cybersecurity leverages AI ML services to assess and correlate events and security threats across multiple sources and turn them into actionable insights that the security team uses for further assessment, response, and reporting. AI uses machine learning algorithms to consistently learn the data that the system assesses.

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ODSC - Open Data Science

SEPTEMBER 15, 2023

With its advanced algorithms and language comprehension, it can navigate complex datasets and distill valuable insights. This synthetic data serves as a viable alternative for training models, testing algorithms, and ensuring privacy compliance. Interested in attending an ODSC event? Learn more about our upcoming events here.

Data Analysis 96

Data Analysis Data Analysis AI AI 96

Snorkel AI

OCTOBER 31, 2023

The Snorkel papers cover a broad range of topics including fairness, semi-supervised learning, large language models (LLMs), and domain-specific models. We are excited to present the following papers and presentations during this year’s event. Characterizing the Impacts of Semi-supervised Learning for Weak Supervision Li et al.

Supervised Learning 52

Supervised Learning AI AI Machine Learning 52

ODSC - Open Data Science

MARCH 8, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. Interested in attending an ODSC event? Learn more about our upcoming events here.

Artificial Intelligence 52

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PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Jump Right To The Downloads Section Understanding Anomaly Detection: Concepts, Types, and Algorithms What Is Anomaly Detection? Looking for the source code to this post?

Clustering 56

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ODSC - Open Data Science

OCTOBER 10, 2024

This event sparked significant advancements in autonomy, not just for self-driving cars but also for the broader field of robotics. In supervised learning , as Francis explained, a robot is trained by being given correct answers for tasks — such as identifying toys from images — over many iterations.

AI 52

AI AI Supervised Learning Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 19, 2023

Then identifying issues that allow fine-tuning of code, optimizing algorithms, and making strategic use of parallel processing. With a full track devoted to NLP and LLMs , you’ll enjoy talks, sessions, events, and more that squarely focus on this fast-paced field. Interested in attending an ODSC event?

Natural Language Processing 98

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How to Learn Machine Learning

MAY 14, 2023

Building a Solid Foundation in Mathematics and Programming To become a successful machine learning engineer, it’s essential to have a strong foundation in mathematics and programming. Mathematics is crucial because machine learning algorithms are built on concepts such as linear algebra, calculus, probability, and statistics.

Machine Learning 52

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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.

Data Analyst 52

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ODSC - Open Data Science

OCTOBER 2, 2023

It can also be used to generate code for specific purposes, such as generating code to implement a specific algorithm or to generate code to solve a specific problem. With a full track devoted to NLP and LLMs , you’ll enjoy talks, sessions, events, and more that squarely focus on this fast-paced field.

Data Science 98

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ODSC - Open Data Science

SEPTEMBER 26, 2023

Synthetic data is artificial data that is created by algorithms. Teams that use synthetic data are in greater control of the data they use so they can even go so far as to create data about rare events or data that is sensitive or confidential, such as with delicate medical information or time-series data.

Data Science 52

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Heartbeat

MARCH 7, 2024

ScikitLLM is interesting because it seamlessly integrates LLMs into your traditional Scikit-learn (Sklearn) library. This means Scikit-LLM brings the power of powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

APRIL 26, 2023

AI algorithms can analyze large data sets containing patient health records and find patterns that can point to a specific disease or condition. Synthetic data and creating better records When creating these AI programs, synthetic data is key to anonymous algorithms since they mimic real-world datasets. But that’s not all.

AI 52

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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?

Deep Learning 52

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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.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

AssemblyAI

NOVEMBER 21, 2022

Finding efficient and fast matrix multiplication algorithms is therefore paramount given that they will supercharge every neural network, potentially allowing us to run models prohibited by our current hardware limitations. Recently, DeepMind devised a method to automatically discover new faster matrix multiplication algorithms.

Algorithm 52

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ODSC - Open Data Science

NOVEMBER 8, 2023

Over the past year, new terms, developments, algorithms, tools, and frameworks have emerged to help data scientists and those working with AI develop whatever they desire. There’s a lot to learn for those looking to take a deeper dive into generative AI and actually develop those tools that others will use.

AI 52

AI AI Natural Language Processing Data Science 52

ODSC - Open Data Science

AUGUST 29, 2023

As industries begin to scale and learn how to fully utilize the power of AI, it’s likely that more and more machine learning engineers will work closely to further refine prompt strategies, curbing biases and advancing human-AI conversations.

Natural Language Processing 98

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Pickl AI

NOVEMBER 4, 2024

Mathematics is critical in Data Analysis and algorithm development, allowing you to derive meaningful insights from data. Linear algebra is vital for understanding Machine Learning algorithms and data manipulation. Calculus Learn to understand derivatives and integrals.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

Supervised Learning 105

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IBM Journey to AI blog

MAY 9, 2023

The emergence of transformers and self-supervised learning methods has allowed us to tap into vast quantities of unlabeled data, paving the way for large pre-trained models, sometimes called “ foundation models.” But this is starting to change. Efficiency and sustainability are core design principles for watsonx.ai.

AI 139

AI AI Data Quality Data Lakes 139

DataRobot Blog

DECEMBER 15, 2022

supervised learning and time series regression). For example, how holidays and events affect forecasting. ML pipelines containing preprocessing steps, modeling algorithms, and post-processing steps. For example, choosing the ‘tourist event’ feature shows us that holding such events results in higher sales.

AI 81

AI AI Exploratory Data Analysis Machine Learning 81

Data Science 101

OCTOBER 31, 2019

Data is carefully analyzed and using mining algorithms, hidden patterns are extracted from the data. The models created using these algorithms could be evaluated against appropriate metrics to verify the model’s credibility. The unusual data points may point to a problem or rare event that can be subject to further investigation.

Data Mining 77

Data Mining Data Mining Data Mining Data Science 77

Google Research AI blog

JULY 23, 2023

Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more.

Machine Learning 77

Machine Learning Machine Learning ML ML 77

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 boundary learning with SVMs.

Machine Learning 77

Machine Learning Machine Learning Python Decision Trees 77

Pickl AI

AUGUST 9, 2024

Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Students should understand the concepts of event-driven architecture and stream processing. Students should learn how to apply machine learning models to Big Data.

Big Data 52

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Heartbeat

SEPTEMBER 20, 2023

This technology has broad applications, including aiding individuals with visual impairments, improving image search algorithms, and integrating optical recognition with advanced language generation to enhance human-machine interactions. Various algorithms are employed in image captioning, including: 1.

Natural Language Processing 52

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

AI 139

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IBM Journey to AI blog

JUNE 14, 2023

With a foundation model, often using a kind of neural network called a “transformer” and leveraging a technique called self-supervised learning, you can create pre-trained models for a vast amount of unlabeled data. This is usually text, but it can also be code, IT events, time series, geospatial data, or even molecules.

AI 105

AI AI Natural Language Processing Data Lakes 105

Towards AI

MARCH 28, 2023

Mapping these farms allows policy-makers to allocate resources and monitor the impacts of extreme events on food production and food security. In this challenge, the objective is to design machine learning algorithms for classifying crop field boundaries using multispectral observations.

Machine Learning 52

Machine Learning Machine Learning Supervised Learning Algorithm 52

Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.

Natural Language Processing 83

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Heartbeat

FEBRUARY 15, 2023

It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. As a machine learning engineer, you start with a labeled data set that has vast amounts of text that have already been categorized.

ML 52

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Snorkel AI

JANUARY 16, 2024

As humans, we learn a lot of general stuff through self-supervised learning by just experiencing the world. The original paper that coined the term “ large language model ” was a 2007 Google paper where they used an algorithm called “Stupid Backoff.” More Snorkel AI events coming! DK: For sure. DK: Thank you.

AI 52

AI AI Supervised Learning Algorithm 52

Heartbeat

FEBRUARY 28, 2023

Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms. U-Net , U-Net++ ], whereas unsupervised learning eliminates this requirement [see this r eview paper ]. What is Semi-supervised Learning (SSL)? Let’s dive in!

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