Pickl AI

OCTOBER 15, 2024

Summary: Statistical Modeling is essential for Data Analysis, helping organisations predict outcomes and understand relationships between variables. Introduction Statistical Modeling is crucial for analysing data, identifying patterns, and making informed decisions. Below are the essential steps involved in the process.

Explainability 52

Explainability Data Analysis Data Quality Categorization 52

Pickl AI

JULY 12, 2023

Data manipulation in Data Science is the fundamental process in data analysis. The data professionals deploy different techniques and operations to derive valuable information from the raw and unstructured data. The objective is to enhance the data quality and prepare the data sets for the analysis.

Data Analysis 52

Data Analysis Data Science Data Quality Python 52

Pickl AI

AUGUST 27, 2024

Methods of Data Collection Data collection methods vary widely depending on the field of study, the nature of the data needed, and the resources available. Here are some common methods: Surveys and Questionnaires Researchers use structured tools like surveys to collect numerical or categorical data from many participants.

Data Analysis 52

Data Analysis Data Integration Categorization Data Quality 52

Pickl AI

SEPTEMBER 12, 2024

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping.

Data Science 52

Data Science Machine Learning Data Mining Algorithm 52

Pickl AI

NOVEMBER 6, 2023

Communication and Storytelling: Data Visualization is an effective way to communicate complex data and findings to both technical and non-technical audiences. Visual representations make it easier to convey information, present key findings, and tell compelling stories derived from data.

Data Scientist 52

Data Scientist Data Science Data Analysis Python 52

Pickl AI

SEPTEMBER 30, 2024

Understanding these pros and cons will help you decide when to effectively utilise Random Forest in your Data Analysis projects. Whether predicting categorical outcomes, such as classifying customer behaviour, or continuous outcomes, like forecasting sales, Random Forest adapts well to different data types.

Algorithm 52

Algorithm Machine Learning Data Scientist Explainability 52

AWS Machine Learning Blog

JULY 31, 2023

This is enabled by setting aside a portion of the historical training data so it can be compared with what the model predicts for those values. In the example of customer churn (which is a categorical classification problem), you start with a historical dataset that describes customers with many attributes (one in each record).

Auto-classification 90

Auto-classification Machine Learning Auto-complete ML 90

Topbots

DECEMBER 19, 2023

The Many Faces of Responsible AI In her presentation , Lora Aroyo, a Research Scientist at Google Research, highlighted a key limitation in traditional machine learning approaches: their reliance on binary categorizations of data as positive or negative examples. The main idea is to use insights from adaptive data analysis.

Computer Vision 52

Computer Vision Natural Language Processing AI Research AI Researcher 52

Dlabs.ai

SEPTEMBER 24, 2024

Instead of applying uniform regulations, it categorizes AI systems based on their potential risk to society and applies rules accordingly. Determine which systems impact EU patients or process EU health data Next, determine which systems impact EU patients or process EU health data.

AI 52

AI AI Explainability Artificial Intelligence 52

DataRobot Blog

DECEMBER 20, 2022

In this educated example , the aim is to predict home prices at the property level in the city of Madrid and the training dataset contains 5 different data types (numerical, categorical, text, location, and images) and +90 variables that are related to these 5 different groups: Market performance. Property performance.

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Explainability Automation Machine Learning AI 59

Chatbots Life

MAY 19, 2023

Without a defined ticket intake process and request tracking technologies, the IT service desk can’t record data that can assist in detecting common issues and speed up future resolution times. Without efficient record-keeping and data analysis tools, help desks spend time and corporate resources researching and resolving the same problems.

Chatbots 95

Chatbots Automation Auto-complete NLP 95

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. All of this work needs to be done in some prioritized way.

Machine Learning 52

Machine Learning Data Scientist Data Science ML 52

Snorkel AI

MAY 12, 2023

Kishore will then double click into some of the opportunities we find here at Capital One, and Bayan will finish us off with a lean into one of our open-source solutions that really is an important contribution to our data-centric AI community. All of this work needs to be done in some prioritized way.

Machine Learning 52

Machine Learning Data Scientist Data Science ML 52

Unite.AI

NOVEMBER 13, 2024

Initially designed for basic calculations and simple data management, their functionality has expanded as the need for data-driven insights has grown. Today, enterprises need real-time data analysis, advanced analytics, and even predictive capabilities within the familiar spreadsheet format.

Large Language Models 147

Large Language Models Data Analysis AI AI 147

AWS Machine Learning Blog

MARCH 29, 2023

Exploratory data analysis After you import your data, Canvas allows you to explore and analyze it, before building predictive models. You can preview your imported data and visualize the distribution of different features. This information can be used to refine your input data and drive more accurate models.

Machine Learning 87

Machine Learning ML Data Science Data Analysis 87

Dlabs.ai

DECEMBER 6, 2022

They’re the perfect fit for: Image, video, text, data & lidar annotation Audio transcription Sentiment analysis Content moderation Product categorization Image segmentation iMerit also specializes in extraction and enrichment for Computer Vision , NLP , data labeling, and other technologies.

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Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 52