ODSC - Open Data Science

AUGUST 25, 2023

Unique Challenges and Opportunities of Artificial Intelligence Applications in Human Resource Functions Editor’s note: Seema Chokshi is a speaker for ODSC APAC this August 22–23. Employees’ negative reactions to surveillance can also give rise to distrust and unwillingness to comply with policies based on algorithmic outcomes.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Algorithm 52

Data Science Dojo

JULY 17, 2023

These methods can help businesses to make sense of their data and to identify trends and patterns that would otherwise be invisible. In recent years, there has been a growing interest in the use of artificial intelligence (AI) for data analysis.

Data Analysis 195

Data Analysis Data Analysis Tableau Machine Learning 195

IBM Data Science in Practice

JANUARY 9, 2024

By Carolyn Saplicki , IBM Data Scientist Industries are constantly seeking innovative solutions to maximize efficiency, minimize downtime, and reduce costs. One groundbreaking technology that has emerged as a game-changer is asset performance management (APM) artificial intelligence (AI).

ML 130

ML ML AI AI 130

PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

K-nearest Neighbors 93

K-nearest Neighbors Algorithm Deep Learning Deep Learning 93

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. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. This process is known as training, and it relies on large amounts of labeled data. How Deep Learning Algorithms Work?

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Towards AI

AUGUST 24, 2023

Common mistakes and misconceptions about learning AI/ML Markus Spiske on Unsplash A common misconception of beginners is that they can learn AI/ML from a few tutorials that implement the latest algorithms, so I thought I would share some notes and advice on learning AI. Trying to code ML algorithms from scratch. I also have an M.S.

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AI AI Algorithm ML 80

Towards AI

JANUARY 31, 2023

Identifying Traditional Nigerian Textiles using Artificial Intelligence on Android Devices ( Part 1 ) Nigeria is a country blessed by God with 3 major ethnic groups( Yoruba, Hausa, and Ibo) and these different ethnic groups have their different cultural differences in terms of dressing, marriage, food, etc.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Dataconomy

SEPTEMBER 13, 2023

In the context of artificial intelligence, diffusion models leverage this idea to generate new data samples that resemble existing data. By iteratively applying a noise schedule to a fixed initial condition, diffusion models can generate diverse outputs that capture the underlying distribution of the training data.

Artificial Intelligence 127

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Towards AI

AUGUST 25, 2023

Describe any data preparation and feature engineering steps that you have done. If you are having coding issues, it is best to share a link to the code/algorithm source and say that you are having problems with the implementation rather than posting code snippets and asking “what is wrong with my code?” Describe the problem.

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Dataconomy

AUGUST 16, 2023

Data scientists are the master keyholders, unlocking this portal to reveal the mysteries within. They wield algorithms like ancient incantations, summoning patterns from the chaos and crafting narratives from raw numbers. Model development : Crafting magic from algorithms!

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Data Scientist Data Science Machine Learning Machine Learning 172

ODSC - Open Data Science

MARCH 13, 2023

Machine learning practitioners tend to do more than just create algorithms all day. First, there’s a need for preparing the data, aka data engineering basics. As the chart shows, two major themes emerged.

Machine Learning 94

Machine Learning Machine Learning Data Wrangling Data Science 94

Towards AI

AUGUST 16, 2023

What is AI Artificial intelligence (AI) focuses on the design and implementation of intelligent systems that perceive, act, and learn in response to their environment. Gungor Basa Technology of Me There is often confusion between the terms artificial intelligence and machine learning.

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AI AI Machine Learning Machine Learning 70

Becoming Human

MAY 12, 2023

The use of Artificial Intelligence (AI) has become increasingly prevalent in the modern world, seeing its potential to drastically improve human life in every way possible. In order to achieve this, one must understand the algorithms and be able to apply them to real-world challenges through AI.

Machine Learning 81

Machine Learning Machine Learning AI AI 81

Flipboard

NOVEMBER 21, 2023

MATLAB   is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. Because we have a model of the system and faults are rare in operation, we can take advantage of simulated data to train our algorithm.

Machine Learning 166

Machine Learning Machine Learning AWS Decision Trees 166

Dataconomy

MARCH 27, 2023

Robotic process automation vs machine learning is a common debate in the world of automation and artificial intelligence. The differences between robotic process automation vs machine learning lie in their functionality, purpose, and the level of human intervention required Is RPA artificial intelligence?

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ML ML Machine Learning Machine Learning 70

Becoming Human

MAY 11, 2023

It covers everything from data preparation and model training to deployment, monitoring, and maintenance. The MLOps process can be broken down into four main stages: Data Preparation: This involves collecting and cleaning data to ensure it is ready for analysis.

Machine Learning 78

Machine Learning Machine Learning Cloud Computing DataOps 78

AWS Machine Learning Blog

NOVEMBER 27, 2023

Generative artificial intelligence ( generative AI ) models have demonstrated impressive capabilities in generating high-quality text, images, and other content. However, these models require massive amounts of clean, structured training data to reach their full potential. This will land on a data flow page.

Data Preparation 92

Data Preparation AI AI Database 92

ODSC - Open Data Science

SEPTEMBER 25, 2023

The tables have the following row counts: Customers: 2 rows Orders: 4 rows Order products: 16 rows Order events: 26 rows Notifications: 10 rows Notification interactions: 15 rows Data preparation and filtering: Data preparation involves removing incorrect or outlier data.

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Data Preparation Machine Learning Machine Learning ML 104

IBM Journey to AI blog

AUGUST 12, 2024

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

Big Data 106

Big Data Big Data ML ML 106

PyImageSearch

OCTOBER 21, 2024

One such technique is the Isolation Forest algorithm, which excels in identifying anomalies within datasets. In this tutorial, you will learn how to implement a predictive maintenance system using the Isolation Forest algorithm — a well-known algorithm for anomaly detection. And Why Anomaly Detection?

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Algorithm Deep Learning Deep Learning Data Preparation 95

Pickl AI

NOVEMBER 5, 2024

Introduction Data Science and Artificial Intelligence (AI) are at the forefront of technological innovation, fundamentally transforming industries and everyday life. Enhanced data visualisation aids in better communication of insights. Domain knowledge is crucial for effective data application in industries.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

AWS Machine Learning Blog

JULY 18, 2023

The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. The BlazingText algorithm expects a single preprocessed text file with space-separated tokens. You now run the data preparation step in the notebook. For instructions, see Create your first S3 bucket.

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Supervised Learning Algorithm Natural Language Processing AWS 80

Towards AI

AUGUST 16, 2023

Michael Dziedzic on Unsplash I am often asked by prospective clients to explain the artificial intelligence (AI) software process, and I have recently been asked by managers with extensive software development and data science experience who wanted to implement MLOps. Norvig, Artificial Intelligence: A Modern Approach, 4th ed.

Machine Learning 74

Machine Learning Machine Learning AI AI 74

Towards AI

APRIL 27, 2023

80% of the time goes in data preparation ……blah blah…. In short, the whole data preparation workflow is a pain, with different parts managed or owned by different teams or people distributed across different geographies depending upon the company size and data compliances required. What is the problem statement?

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Data Preparation ML ML AI 74

Tableau

FEBRUARY 22, 2021

release, we’re delivering the first integration of Salesforce’s artificial intelligence (AI) and machine learning (ML) capabilities in Tableau. We’re bringing powerful data science techniques closer to the business, beginning with Einstein Discovery in Tableau. Product Management Director, Tableau CRM. Spencer Czapiewski.

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Flipboard

NOVEMBER 21, 2024

We use Amazon SageMaker Pipelines , which helps automate the different steps, including data preparation, fine-tuning, and creating the model. This configuration acts as a guide, helping SageMaker Autopilot understand the nature of your problem and select the most appropriate algorithm or approach.

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Pickl AI

SEPTEMBER 10, 2024

AI-powered features in Excel enable users to make data-driven decisions more efficiently, saving time and effort while uncovering valuable insights hidden within large datasets. Introduction Artificial Intelligence (AI) is revolutionising how we use Excel, making data management faster and more efficient.

Power BI 52

Power BI Data Analysis Data Analysis AI 52

AWS Machine Learning Blog

JUNE 3, 2024

SageMaker Data Wrangler has also been integrated into SageMaker Canvas, reducing the time it takes to import, prepare, transform, featurize, and analyze data. In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing.

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AWS Machine Learning Blog

AUGUST 26, 2024

GenASL is a generative artificial intelligence (AI) -powered solution that translates speech or text into expressive ASL avatar animations, bridging the gap between spoken and written language and sign language. This instance will be used for various tasks such as video processing and data preparation.

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AWS AI AI ML 116

Pickl AI

OCTOBER 3, 2024

Summary: Artificial Intelligence Models as a Service (AIMaaS) provides cloud-based access to scalable, customizable AI models. Introduction to AIMaaS Artificial Intelligence Models as a Service (AIMaaS) represents a transformative approach in the deployment of AI technologies.

AI 52

AI AI Machine Learning Machine Learning 52

AWS Machine Learning Blog

JUNE 17, 2024

Being one of the largest AWS customers, Twilio engages with data and artificial intelligence and machine learning (AI/ML) services to run their daily workloads. The rise of generative AI increases the demand for training, deploying, and running ML models, and consequently, the use of data.

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ML ML AWS Machine Learning 117

Towards AI

JUNE 27, 2023

In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role. Its functionalities span from deep learning to text mining, data preparation, and predictive analytics, ensuring a versatile utility for developers and data scientists alike.

Machine Learning 84

Machine Learning Machine Learning ML ML 84

Precisely

SEPTEMBER 26, 2024

It doesn’t seem like long ago that we thought of artificial intelligence (AI) as a futuristic concept—but today, it’s here in full swing, and organizations across sectors are working to integrate it into their core processes. The real challenge lies in ensuring that the data powering your projects is AI-ready.

AI 75

AI AI Data Governance Data Quality 75

Pickl AI

DECEMBER 24, 2024

Introduction In the rapidly evolving landscape of Artificial Intelligence (AI), Retrieval-Augmented Generation (RAG) has emerged as a transformative approach that enhances the capabilities of language models. Each vector represents specific features or characteristics of the data, allowing for efficient storage and retrieval.

Database 52

Database Machine Learning Machine Learning AI 52

Becoming Human

MAY 15, 2023

With the help of web scraping, you can make your own data set to work on. Machine Learning Machine learning is a type of artificial intelligence that allows software applications to learn from the data and become more accurate over time.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Towards AI

AUGUST 16, 2023

Figure 4: The ModelOps process [Wikipedia] The Machine Learning Workflow Machine learning requires experimenting with a wide range of datasets, data preparation, and algorithms to build a model that maximizes some target metric(s).

Machine Learning 82

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