Dataconomy

JUNE 13, 2023

In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. Decision intelligence is an innovative approach that blends the realms of data analysis, artificial intelligence, and human judgment to empower businesses with actionable insights.

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Dataconomy

JULY 18, 2023

By leveraging artificial intelligence algorithms and data analytics, manufacturers can streamline their quoting process, improve accuracy, and gain a competitive edge in the market. These techniques enable businesses to respond quickly to customer inquiries, optimize pricing strategies, and automate the quotation generation process.

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Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Naïve Bayes algorithms include decision trees , which can actually accommodate both regression and classification algorithms.

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Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. At the same time, Keras is a high-level neural network API that runs on top of TensorFlow and simplifies the process of building and training deep learning models.

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ODSC - Open Data Science

AUGUST 15, 2023

Big Data Analysis with PySpark Bharti Motwani | Associate Professor | University of Maryland, USA Ideal for business analysts, this session will provide practical examples of how to use PySpark to solve business problems. Finally, you’ll discuss a stack that offers an improved UX that frees up time for tasks that matter.

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Pickl AI

MAY 10, 2023

K-Nearest Neighbours (kNN) In order to calculate the distance between one data point and every other accomplished parameter through using the metrics of distance like Euclidean distance, Manhattan distance and others. Decision Trees Decision Trees are non-linear model unlike the logistic regression which is a linear model.

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Pickl AI

JANUARY 29, 2024

ML focuses on enabling computers to learn from data and improve performance over time without explicit programming. Key Components In Data Science, key components include data cleaning, Exploratory Data Analysis, and model building using statistical techniques. billion in 2022 to a remarkable USD 484.17

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IBM Journey to AI blog

JUNE 5, 2024

Using comprehensive, AI-driven SaaS analytics, businesses can make data-driven decisions about feature enhancements, UI/UX improvements and marketing strategies to maximize user engagement and meet—or exceed—business goals. AI technologies can also reveal and visualize data patterns to help with feature development.

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Pickl AI

OCTOBER 18, 2023

Data serves as the backbone of informed decision-making, and the accuracy, consistency, and reliability of data directly impact an organization’s operations, strategy, and overall performance. Informed Decision-making High-quality data empowers organizations to make informed decisions with confidence.

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Pickl AI

JULY 23, 2023

Data Processing Data processing involves cleaning, transforming, and organizing the collected data to prepare it for analysis. This step is crucial for eliminating inconsistencies and ensuring data integrity. Data Analysis Data analysis is the heart of deriving insights from the gathered information.

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Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

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Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling. Suppose you want to develop a classification model to predict customer churn.

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Pickl AI

DECEMBER 4, 2024

Augmented Analytics Augmented analytics is revolutionising the way businesses analyse data by integrating Artificial Intelligence (AI) and Machine Learning (ML) into analytics processes. Understand data structures and explore data warehousing concepts to efficiently manage and retrieve large datasets.

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Pickl AI

FEBRUARY 7, 2025

These networks can automatically discover patterns and features without explicit programming, making deep learning ideal for tasks requiring high levels of complexity, such as speech recognition and natural language processing. Manufacturing: Predictive maintenance and quality control processes are streamlined using ML models.

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Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). Depending on the data they are provided, different classifiers may perform better or worse (eg. A random forest is an ensemble classifier that makes predictions using a variety of decision trees. Uysal and Gunal, 2014).

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Pickl AI

NOVEMBER 18, 2024

Predictive analytics uses historical data to forecast future trends, such as stock market movements or customer churn. Natural language processing ( NLP ) allows machines to understand, interpret, and generate human language, which powers applications like chatbots and voice assistants.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

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Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Together, Data Science and AI enable organisations to analyse vast amounts of data efficiently and make informed decisions based on predictive analytics.

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Cambridge Intelligence

FEBRUARY 20, 2024

FREE: Managing fraud The ultimate guide to fraud detection, investigation and prevention using data visualization GET YOUR FREE GUIDE The role of new & existing technology For many years, credit card companies have relied on analytics, algorithms and decision trees to power their fraud strategy.

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Pickl AI

AUGUST 23, 2023

Consider enrolling in a “Data Science for stock market” course, which can provide insights into the specific techniques, tools, and datasets relevant to financial markets. Project-based Learning Hands-on experience is invaluable when it comes to Data Science.

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Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use. Boosting can help to improve the accuracy and generalization of the final model.

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Pickl AI

JULY 18, 2023

Its simplicity, versatility, and extensive range of libraries make it a favorite choice among Data Scientists. However, with libraries like NumPy, Pandas, and Matplotlib, Python offers robust tools for data manipulation, analysis, and visualization. SAS provides a wide range of statistical procedures and algorithms.

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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. These components solve complex problems and drive decision-making in various industries.

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Pickl AI

NOVEMBER 28, 2024

Decision Trees These trees split data into branches based on feature values, providing clear decision rules. These networks can learn from large volumes of data and are particularly effective in handling tasks such as image recognition and natural language processing.

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