ODSC - Open Data Science

FEBRUARY 6, 2023

Intro to Deep Learning with PyTorch and TensorFlow Dr. Jon Krohn | Chief Data Scientist | Nebula.io In recent years, Deep Learning has become ubiquitous across a wide range of data-driven applications.

Data Science 98

Data Science Categorization Data Scientist Deep Learning 98

Marktechpost

SEPTEMBER 8, 2023

Microsoft Power BI Microsoft Power BI, a powerful business intelligence platform that lets users filter through data and visualize it for insights, is another top AI tool for data analysis. Users may import data from practically anywhere into the platform and immediately create reports and dashboards.

AI Tools 132

AI Tools Data Science Machine Learning Data Analysis 132

Pickl AI

OCTOBER 14, 2024

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

Data Analysis 52

Data Analysis Data Mining Data Discovery Machine Learning 52

Pickl AI

AUGUST 29, 2023

Data Scientists are highly in demand across different industries for making use of the large volumes of data for analysisng and interpretation and enabling effective decision making. One of the most effective programming languages used by Data Scientists is R, that helps them to conduct data analysis and make future predictions.

Data Scientist 52

Data Scientist Data Analysis Data Science Machine Learning 52

Flipboard

MARCH 22, 2023

Data Wrangler simplifies the data preparation and feature engineering process, reducing the time it takes from weeks to minutes by providing a single visual interface for data scientists to select and clean data, create features, and automate data preparation in ML workflows without writing any code.

IDP 123

IDP Data Scientist Categorization Data Quality 123

Towards AI

FEBRUARY 3, 2024

As a data scientist, we will explore the entire data set to understand each characteristic and identify any patterns existing if any in it. This process is called Exploratory Data Analysis(EDA). Step III: Data organization and Feature Engineering This is a crucial step to get accurate results.

Machine Learning 122

Machine Learning Data Scientist NLP ML 122

IBM Journey to AI blog

AUGUST 28, 2023

Information retrieval The first step in the text-mining workflow is information retrieval, which requires data scientists to gather relevant textual data from various sources (e.g., The data collection process should be tailored to the specific objectives of the analysis. positive, negative or neutral).

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

ODSC - Open Data Science

FEBRUARY 6, 2023

Monitoring and Compliance Nonprofits can use benchmarking and data science to measure their operations’ effectiveness precisely and customize their workflows for improved outcomes. Real-time tracking during emergencies and optimizing rescue efforts can benefit greatly from data analysis and visualization.

Data Science 97

Data Science Data Scientist Natural Language Processing NLP 97

Pickl AI

AUGUST 1, 2023

Moreover, using sentiment analysis techniques, organizations can gain valuable insights into customer satisfaction, identify trends, and make data-driven improvements. Topic Modeling With text mining, it is possible to identify and categorize topics and themes within large collections of documents. Wrapping it up !!!

Data Analysis 52

Data Analysis Python Categorization Data Mining 52

ODSC - Open Data Science

MARCH 13, 2023

Dr. Jon Krohn Chief Data Scientist | Nebula.io He also shares his expertise with the data science community at conferences. However, our speakers are also experienced and acclaimed instructors, able to impart their knowledge in a manner that is engaging and effective.

Data Science 80

Data Science Deep Learning Machine Learning Software Engineer 80

Marktechpost

AUGUST 27, 2024

Data analysis helps organizations make informed decisions by turning raw data into actionable insights. With businesses increasingly relying on data-driven strategies, the demand for skilled data analysts is rising. You’ll learn the fundamentals of gathering, cleaning, analyzing, and visualizing data.

Data Analysis 57

Data Analysis Python Data Scientist ETL 57

Pickl AI

DECEMBER 3, 2024

It involves steps like handling missing values, normalizing data, and managing categorical features, ultimately enhancing model performance and ensuring data quality. Introduction Data preprocessing is a critical step in the Machine Learning pipeline, transforming raw data into a clean and usable format.

Python 52

Python ML Categorization Machine Learning 52

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. The platform makes collaborative data science better for corporate users and simplifies predictive analytics for professional data scientists.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Snorkel AI

NOVEMBER 13, 2024

This definition covers everything from the point of acquiring data to the point at which a data scientist exports a model for deployment. For most of machine learning’s history, data scientists treated data as a static resource; it came pre-labeled by business or data collection processes.

Data Science 52

Data Science Data Scientist Large Language Models Categorization 52

Snorkel AI

NOVEMBER 13, 2024

This definition covers everything from the point of acquiring data to the point at which a data scientist exports a model for deployment. For most of machine learning’s history, data scientists treated data as a static resource; it came pre-labeled by business or data collection processes.

Data Science 52

Data Science Data Scientist Large Language Models Categorization 52

Snorkel AI

NOVEMBER 13, 2024

This definition covers everything from the point of acquiring data to the point at which a data scientist exports a model for deployment. For most of machine learning’s history, data scientists treated data as a static resource; it came pre-labeled by business or data collection processes.

Data Science 52

Data Science Data Scientist Large Language Models Categorization 52

Mlearning.ai

JULY 17, 2023

It natively supports only numerical data, so typically an encoding is applied first for converting the categorical data into a numerical form. Shallow and Deep Clustering Clustering algorithms can be categorized into two types based on their approach to learning: shallow learning and deep learning. this link ).

Categorization 52

Categorization Algorithm Deep Learning Data Analysis 52

ODSC - Open Data Science

APRIL 10, 2023

Deep Learning with PyTorch and TensorFlow part 1 and 2 Dr. Jon Krohn | Chief Data Scientist | Nebula.io Jon Krohn | Chief Data Scientist | Nebula.io Intermediate Machine Learning with scikit-learn: Pandas Interoperability, Categorical Data, Parameter Tuning, and Model Evaluation Thomas J.

Software Engineer 52

Software Engineer Categorization Data Science Machine Learning 52

Viso.ai

DECEMBER 20, 2023

Supervised learning is a type of machine learning algorithm that learns from a set of training data that has been labeled training data. Evaluate the model: After training, the model evaluation is required to determine how well it performs on new, unlabeled data. What is supervised learning?

Computer Vision 98

Computer Vision Machine Learning Neural Network Algorithm 98

Pickl AI

JANUARY 3, 2024

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. Through Exploratory Data Analysis , imputation, and outlier handling, robust models are crafted. Encoding categorical variables: The language of algorithms Machines comprehend numbers, not labels.

Machine Learning 52

Machine Learning Categorization Algorithm Data Analysis 52

Artificial Corner

AUGUST 29, 2023

This time, I embarked on a Data Science journey with British Airways (BA). As a data scientist at BA, our job will be to apply our data analysis and machine learning skills to derive insights that help BA drive revenue upwards. This is a perfect way to showcase your skills and build up your portfolio!

Natural Language Processing 97

Natural Language Processing Machine Learning Data Analysis Data Science 97

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. R’s workflow support enhances productivity and collaboration among data scientists.

Data Science 52

Data Science Data Scientist Machine Learning Data Analysis 52

Becoming Human

MAY 15, 2023

These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey. Data Analysis After learning math now, you are able to talk with your data.

Data Science 75

Data Science Neural Network Machine Learning Python 75

Pickl AI

DECEMBER 14, 2023

So, for anyone who is looking forward to making a career in Data Science, having mathematical expertise is paramount. Through this blog, we take you through the prerequisites of mathematics for Data science and other skills that will make you a successful Data scientist. Why Data Science?

Data Science 52

Data Science Machine Learning Data Analysis Data Scientist 52

Snorkel AI

JULY 3, 2023

Jason Goldfarb, senior data scientist at State Farm , gave a presentation entitled “Reusable Data Cleaning Pipelines in Python” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. It has always amazed me how much time the data cleaning portion of my job takes to complete.

Categorization 52

Categorization Data Scientist Machine Learning Python 52

Snorkel AI

JULY 3, 2023

Jason Goldfarb, senior data scientist at State Farm , gave a presentation entitled “Reusable Data Cleaning Pipelines in Python” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. It has always amazed me how much time the data cleaning portion of my job takes to complete.

Categorization 52

Categorization Data Scientist Machine Learning Python 52

Snorkel AI

JULY 3, 2023

Jason Goldfarb, senior data scientist at State Farm , gave a presentation entitled “Reusable Data Cleaning Pipelines in Python” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. It has always amazed me how much time the data cleaning portion of my job takes to complete.

Categorization 52

Categorization Data Scientist Machine Learning Python 52

Pickl AI

AUGUST 31, 2023

Introduction Python is the most popularly used programming language by Data Scientists that help them in conducting different operations and tasks from simple scripting to complex web application development and data analysis. The following blog will help you understand the process of tabulation of data in Python.

Python 52

Python Data Analysis Data Science Categorization 52

ODSC - Open Data Science

AUGUST 8, 2023

At ODSC West’s Mini-Bootcamp , from October 30th to November 2nd, you’ll have the opportunity to explore many different topics, build new skills and connect with data scientists and experts from a wide range of disciplines in just 4 days and for a lower cost. What is included in a Mini-Bootcamp Pass? Discover below.

Data Science 52

Data Science Deep Learning Machine Learning Python 52

Pickl AI

NOVEMBER 6, 2023

Here are some reasons highlighting the significance of Data Visualization in Data Science: Data Understanding and Exploration: Data Visualization helps in gaining a deeper understanding of the data by visually representing patterns, trends, and relationships that may not be apparent in raw data.

Data Science 52

Data Science Data Scientist Data Analysis Python 52

Viso.ai

MARCH 27, 2024

Participate in Tutorial Kaggle Competitions (Compete with Fellow Kagglers) Kaggle competitions are categorized into different types. Before undertaking an independent data science project, try to complete Knowledge competitions (for knowledge purposes only) and collaborate with fellow data scientists.

Computer Vision 52

Computer Vision Data Scientist Data Science Machine Learning 52

TheSequence

NOVEMBER 20, 2023

In this guest post, Jimmy Whitaker, Data Scientist in Residence at Human Signal, focuses on guiding users in building an agent using the Adala framework. He dives into the integration of Large Language Model-based agents for automating data pipelines, particularly for tasks like data labeling.

Categorization 52

Categorization LLM Large Language Models Data Scientist 52

Pickl AI

AUGUST 16, 2024

Researchers across disciplines will find valuable insights to enhance their Data Analysis skills and produce credible, impactful findings. Introduction Statistical tools are essential for conducting data-driven research across various fields, from social sciences to healthcare.

Data Analysis 52

Data Analysis Python Machine Learning Artificial Intelligence 52

Pickl AI

APRIL 11, 2023

Statistics and statistical analysis are integral when it comes to Data Science. It is the underpinning of the successful analysis of any data set. Studying these variables and drawing inferences is the core task of a Data Scientists. These variables can be used for analyzing trends, and patterns in data.

Data Science 52

Data Science Data Scientist Categorization Data Analysis 52

Pickl AI

NOVEMBER 27, 2024

Python for Data Science Python has become the go-to programming language for Data Science due to its simplicity, versatility, and powerful libraries. It is widely recognised for its role in Machine Learning, data manipulation, and automation, making it a favourite among Data Scientists, developers, and researchers.

Data Science 52

Data Science Python Machine Learning Data Scientist 52

Pickl AI

AUGUST 8, 2024

Understanding their differences helps data scientists choose the right tool for creating compelling visualisations that effectively communicate insights. Introduction Data visualisation is a crucial aspect of Data Analysis, enabling researchers and analysts to interpret complex datasets and communicate findings effectively.

Python 52

Python Data Analysis Categorization Data Scientist 52

Pickl AI

JULY 3, 2024

Both agglomerative and divisive methods offer unique ways to explore data structure and uncover hidden patterns. Understanding these approaches helps choose the right method for different types of data analysis. You can apply it to numeric, categorical, or even a mix of both.

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Categorization Algorithm Data Analysis Machine Learning 52