Data Science Dojo

AUGUST 28, 2023

Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM. Why is LLMOps Essential?

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Dataconomy

JULY 10, 2023

For example, a retailer might use decision intelligence to track customer behavior in real-time and make adjustments to its inventory levels accordingly. Artificial intelligence is both Yin and Yang It also can help organizations make better decisions by providing them with a more holistic view of the data.

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ODSC - Open Data Science

APRIL 25, 2023

Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Be sure to check out her talk, “ Hands-on Data-Centric AI: Data preparation tuning — why and how? Given that data has higher stakes , it only means that you should invest most of your development investment in improving your data quality.

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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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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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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.

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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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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.

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Smart Data Collective

NOVEMBER 9, 2022

As a result of the activity of artificial intelligence, the machine learns, remembers, and reproduces the correct option. ML opens up new opportunities for computers to solve tasks previously performed by humans and trains the computer system to make accurate predictions when inputting data.

Machine Learning 122

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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. 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?

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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).

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Flipboard

MAY 1, 2023

Today, we are happy to announce that with Amazon SageMaker Data Wrangler , you can perform image data preparation for machine learning (ML) using little to no code. Data Wrangler reduces the time it takes to aggregate and prepare data for ML from weeks to minutes. Choose Import. This can take a few minutes.

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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.

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ODSC - Open Data Science

OCTOBER 29, 2024

Classification algorithms are some of the most useful machine learning models in use today. A confusion matrix is a chart that compares the predicted labels of a classification algorithm to their actual value. Confusion matrices do just that for classification algorithms. Many classification tasks naturally involve imbalance.

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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.

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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.

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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.

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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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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.

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AWS Machine Learning Blog

JULY 29, 2024

Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time series forecasts. With SageMaker Canvas, you get faster model building , cost-effective predictions, advanced features such as a model leaderboard and algorithm selection, and enhanced transparency.

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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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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.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

Use case and model lifecycle governance overview In the context of regulations such as the European Union’s Artificial Intelligence Act (EU AI Act), a use case refers to a specific application or scenario where AI is used to achieve a particular goal or solve a problem. An experiment collects multiple runs with the same objective.

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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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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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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.

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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.

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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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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.

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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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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.

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Towards AI

MAY 8, 2024

Created by the author with DALL E-3 Google Earth Engine for machine learning has just gotten a new face lift, with all the advancement that has been going on in the world of Artificial intelligence, Google Earth Engine was not going to be left behind as it is an important tool for spatial analysis.

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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.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

This session covers the technical process, from data preparation to model customization techniques, training strategies, deployment considerations, and post-customization evaluation. Explore how this powerful tool streamlines the entire ML lifecycle, from data preparation to model deployment.

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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

NOVEMBER 15, 2024

It offers an unparalleled suite of tools that cater to every stage of the ML lifecycle, from data preparation to model deployment and monitoring. The platform’s strength lies in its ability to abstract away the complexities of infrastructure management, allowing you to focus on innovation rather than operational overhead.

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