ODSC - Open Data Science

JANUARY 5, 2024

Without this library, data analysis wouldn’t be the same without pandas, which reign supreme with its powerful data structures and manipulation tools. Pandas provides a fast and efficient way to work with tabular data. It is widely used in data science, finance, and other fields where data analysis is essential.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

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.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Ocean Protocol

MARCH 11, 2024

METAR, Miami International Airport (KMIA) on March 9, 2024, at 15:00 UTC In the recently concluded data challenge hosted on Desights.ai , participants used exploratory data analysis (EDA) and advanced artificial intelligence (AI) techniques to enhance aviation weather forecasting accuracy.

Exploratory Data Analysis 52

Exploratory Data Analysis Machine Learning Machine Learning EDA 52

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

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.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

OCTOBER 3, 2024

Predictive analytics refers to the use of statistical algorithms and Machine Learning techniques to analyse historical data and predict future events or outcomes. It involves various processes, including data mining, predictive modelling, and statistical analysis. What is Predictive Analytics?

Predictive Analytics 52

Predictive Analytics Analytics Analytics Machine Learning 52

Pickl AI

DECEMBER 12, 2024

Introduction Boosting is a powerful Machine Learning ensemble technique that combines multiple weak learners, typically decision trees, to form a strong predictive model. Lets explore the mathematical foundation, unique enhancements, and tree-pruning strategies that make XGBoost a standout algorithm. Lower values (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

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.

Machine Learning 59

Machine Learning Machine Learning AI AI 59

ODSC - Open Data Science

OCTOBER 23, 2024

ODSC West is right around the corner, promising an impressive lineup of industry leaders who will cover cutting-edge developments in AI, machine learning, and data science. Many of these speakers are familiar faces at past ODSC events or are regular contributors to major AI and tech conferences.

Data Science 40

Data Science Data Scientist AI AI 40

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. Overfitting: The model performs well only for the sample training data.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

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.

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

Pickl AI

SEPTEMBER 3, 2023

Anomaly Detection in Machine Learning: An approach to data analysis and Machine Learning called “anomaly detection,” also referred to as “outlier detection,” focuses on finding data points or patterns that considerably differ from what is considered to be “normal” or anticipated behaviour.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Dataconomy

FEBRUARY 24, 2023

It could be anything from customer service to data analysis. Collect data: Gather the necessary data that will be used to train the AI system. This data should be relevant, accurate, and comprehensive. Several algorithms are available, including decision trees, neural networks, and support vector machines.

Artificial Intelligence 91

Artificial Intelligence Artificial Intelligence AI AI 91

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.

Data Quality 52

Data Quality ML ML Machine Learning 52

Heartbeat

SEPTEMBER 28, 2023

In a typical MLOps project, similar scheduling is essential to handle new data and track model performance continuously. Load and Explore Data We load the Telco Customer Churn dataset and perform exploratory data analysis (EDA). Random Forest Classifier (rf): Ensemble method combining multiple decision trees.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines ML 52

Heartbeat

FEBRUARY 8, 2023

R is frequently used for statistical software development, data analysis, and data visualisation because it can handle large data sets with ease. This programming language offers a variety of methods for model training and evaluation, making it perfect for machine learning projects that need a lot of data processing.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning Deep Learning 52

Dataconomy

SEPTEMBER 1, 2023

Heart disease stands as one of the foremost global causes of mortality today, presenting a critical challenge in clinical data analysis. Leveraging hybrid machine learning techniques, a field highly effective at processing vast healthcare data volumes is increasingly promising in effective heart disease prediction.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195

Mlearning.ai

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Deep Learning 78

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. They may also struggle to fully leverage the predictive capabilities of app analytics.

Analytics 94

Analytics Analytics ML ML 94

Pickl AI

JUNE 6, 2024

Enter predictive modeling , a powerful tool that harnesses the power of data to anticipate what tomorrow may hold. Predictive modeling is a statistical technique that uses Data Analysis to make informed forecasts about future events. However, raw data is often messy and needs cleaning and transformation to be usable.

Internet of Things 52

Internet of Things Data Scientist Data Quality Data Analysis 52