Unite.AI

JANUARY 7, 2025

Fermata , a trailblazer in data science and computer vision for agriculture, has raised $10 million in a Series A funding round led by Raw Ventures. Key Features of Croptimus Automated Pest and Disease Detection: Identifies issues like aphids, spider mites, powdery mildew, and mosaic virus before they become critical.

Computer Vision 182

Computer Vision Actionable Intelligence Continuous Learning AI 182

Towards AI

NOVEMBER 6, 2024

Performing exploratory data analysis to gain insights into the dataset’s structure. Whether you’re a data scientist aiming to deepen your expertise in NLP or a machine learning engineer interested in domain-specific model fine-tuning, this tutorial will equip you with the tools and insights you need to get started.

BERT 111

BERT Automation NLP Data Analysis 111

IBM Journey to AI blog

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. What is MLOps?

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Data Science 175

Data Science Machine Learning Big Data Data Mining 175

Artificial Corner

MAY 31, 2023

Super fast data analysis in ChatGPT. Continue reading on Artificial Corner »

Data Analysis 124

Data Analysis ChatGPT Automation Data Science 124

Marktechpost

MAY 15, 2024

In the vast world of data science, countless tools are available to help analysts and researchers make sense of data and build powerful machine-learning models. Whether one is working on regression or classification tasks, LazyPredict streamlines the process and helps find the best model for the data.

Data Science 123

Data Science Python Machine Learning Data Analysis 123

Unite.AI

FEBRUARY 12, 2025

AI integration (the Mr. Peasy chatbot) further enhances user experience by providing quick, automated support and data retrieval. The Manufacturing app handles BOMs (Bills of Materials), routing, and production orders, allowing companies to automate workflows from materials procurement through final assembly.

AI Tools 261

AI Tools Machine Learning Auto-complete AI 261

IBM Journey to AI blog

OCTOBER 23, 2024

Conversely, SPSS Statistics professionals value its user-friendly interface, low learning curve for rapid proficiency in statistical procedures and extensive range of data analysis and modeling techniques. Many data analytics and data science experts know the individual strengths of IBM SPSS Statistics, R and Python.

Python 219

Python Data Analysis Data Science Machine Learning 219

Analytics Vidhya

FEBRUARY 2, 2024

Its simplicity and extensive libraries make it a go-to choice for diverse applications, from data analysis, machine learning, and web development to automation and scripting. Introduction Python offers developers a wide range of functionalities.

Python 305

Python Data Analysis Machine Learning Automation 305

Towards AI

JANUARY 22, 2025

Simply put, focusing solely on data analysis, coding or modeling will no longer cuts it for most corporate jobs. My personal opinion: its more important than ever to be an end-to-end data scientist. You have to understand data, how to extract value from them and how to monitor model performances. What to do then?

Data Scientist 105

Data Scientist Data Drift Data Science Data Analysis 105

Marktechpost

DECEMBER 18, 2024

AI-powered tools have become indispensable for automating tasks, boosting productivity, and improving decision-making. It automates code documentation and integrates seamlessly with AWS services, simplifying deployment processes. It automates model development and scales predictive analytics for businesses across industries.

Software Development 103

Software Development AI Tools DevOps Machine Learning 103

Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

Data Science 116

Data Science ML ML Engineer Data Scientist 116

Artificial Corner

JANUARY 7, 2025

Photo by Austin Distel on Unsplash In this article, I will show you 3 books that helped me automate tasks such as sending emails, collecting data, creating reports, and more! Automate the Boring Stuff with Python This is a book that I think many have heard of. Subscribe now 2.

Automation 98

Automation Python Data Scientist Data Analysis 98

IBM Journey to AI blog

NOVEMBER 13, 2023

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

DevOps 323

DevOps Software Development Automation Machine Learning 323

Marktechpost

DECEMBER 24, 2023

Data exploration is an important step in data analysis that extracts key insights using multiple steps such as filtering, sorting, grouping, etc. However, this process is generally interactive and requires the user to manually explore the data, making the process time-consuming and necessitating domain expertise.

LLM 133

LLM Automation Insight Engine Data Analysis 133

ODSC - Open Data Science

FEBRUARY 2, 2023

Here’s what we found for both skills and platforms that are in demand for data scientist jobs. Data Science Skills and Competencies Aside from knowing particular frameworks and languages, there are various topics and competencies that any data scientist should know. Joking aside, this does infer particular skills.

Data Science 98

Data Science Data Scientist Big Data Machine Learning 98

ODSC - Open Data Science

SEPTEMBER 15, 2023

From uncovering hidden patterns to providing actionable recommendations, generative AI’s proficiency in data analytics heralds a new era where innovation spans the spectrum from artistic expression to informed business strategies. So let’s take a brief look at some examples of how generative AI can be used for data analytics.

Data Analysis 96

Data Analysis Generative AI Data Science AI 96

AI News

OCTOBER 15, 2024

By leveraging vast amounts of data and powerful algorithms, ML enables companies to automate processes, make accurate predictions, and uncover hidden patterns to optimise performance. Providing training data, and using data science will allow chatbots to communicate with customers.

Machine Learning 290

Machine Learning Chatbots Business Intelligence Automation 290

Pickl AI

MAY 30, 2024

Summary: The Data Science and Data Analysis life cycles are systematic processes crucial for uncovering insights from raw data. Quality data is foundational for accurate analysis, ensuring businesses stay competitive in the digital landscape. billion INR by 2026, with a CAGR of 27.7%.

Data Analysis 52

Data Analysis Data Science Data Scientist Data Quality 52

Pickl AI

MARCH 10, 2025

Summary: Microsoft Excel offers essential features for data organisation, analysis, and visualisation. Excel enhances productivity across industries with built-in formulas, charts, pivot tables, automation, and cloud collaboration. Automation with VBA macros and real-time collaboration improve productivity and efficiency.

Data Analysis 52

Data Analysis Automation Data Science Python 52

Towards AI

SEPTEMBER 7, 2023

Four Essential Tools Every Data Scientist Should Have in Their Toolbox This member-only story is on us. Photo by Adam Śmigielski on Unsplash It’s a great time to be a data scientist! What takes a lot of time to put together can be automated now, leaving much room to improve insights-creation and the machine learning model design.

Data Analysis 128

Data Analysis Data Scientist Machine Learning Automation 128

Towards AI

JANUARY 27, 2023

In the increasingly competitive world, understanding the data and taking quicker actions based on that help create differentiation for the organization to stay ahead! It is used to discover trends [2], patterns, relationships, and anomalies in data, and can help inform the development of more complex models [3].

Data Analysis 98

Data Analysis Data Science Software Engineer Business Intelligence 98

Analytics Vidhya

JANUARY 25, 2023

Well, the secret is in the field of Automated Machine Learning (AutoML). Introduction Source – mccinnovations.com Do you ever wonder how companies develop and train machine learning models without experts?

Machine Learning 361

Machine Learning Automation Data Analysis Data Science 361

Analytics Vidhya

MAY 15, 2024

For many uses, such as competitive analysis, market research, and basic data collection for analysis, efficiently extracting data from websites is crucial. Tradition-based manual data collection methods can be time-consuming and unproductive.

Automation 317

Automation Data Mining Data Analysis Data Science 317

Flipboard

AUGUST 1, 2023

• Falcon LLM: The New King of Open-Source LLMs • 10 ChatGPT Plugins for Data Science Cheat Sheet • ChatGPT for Data Science Interview Cheat Sheet • Noteable Plugin: The ChatGPT Plugin That Automates Data Analysis • 3 Ways to Access Claude AI for Free • What are Vector Databases and Why Are They Important for LLMs? •

ChatGPT 123

ChatGPT Data Analysis Data Science LLM 123

Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

Data Science 75

Data Science Neural Network Machine Learning Python 75

AWS Machine Learning Blog

OCTOBER 16, 2024

This post shows how DPG Media introduced AI-powered processes using Amazon Bedrock and Amazon Transcribe into its video publication pipelines in just 4 weeks, as an evolution towards more automated annotation systems. The following were some initial challenges in automation: Language diversity – The services host both Dutch and English shows.

Metadata 117

Metadata Automation Generative AI AI 117

Towards AI

MARCH 11, 2025

Lets find to what extent your data science work is automated! The year is 2025, and your data science competition isnt just the team down the hall its the people whove mastered Googles Gemini Data Science Agent. And with this Data Science Agent, its no different. Not a member?Feel

Data Science 67

Data Science Automation AI AI 67

IBM Journey to AI blog

OCTOBER 20, 2023

AI platforms offer a wide range of capabilities that can help organizations streamline operations, make data-driven decisions, deploy AI applications effectively and achieve competitive advantages. AutoML tools: Automated machine learning, or autoML, supports faster model creation with low-code and no-code functionality.

Machine Learning 225

Machine Learning Automation AI AI 225

Towards AI

APRIL 7, 2024

This article seeks to also explain fundamental topics in data science such as EDA automation, pipelines, ROC-AUC curve (how results will be evaluated), and Principal Component Analysis in a simple way. Automation helps team members focus on more strategic and demanding tasks.

Machine Learning 124

Machine Learning Data Analysis Data Science Automation 124

Marktechpost

JULY 5, 2024

Programming for Data Science with Python This course series teaches essential programming skills for data analysis, including SQL fundamentals for querying databases and Unix shell basics. The curriculum also includes classical search, automated planning, and probabilistic graphical models for comprehensive AI training.

Data Science 61

Data Science Machine Learning Data Analysis Software Engineer 61

Flipboard

AUGUST 12, 2023

If you’ve ever had to generate or present reports, regardless of their intent – be it for business, personal purposes, or data analysis – you’re …

Automation 123

Automation Data Analysis ChatGPT Data Science 123

Unite.AI

SEPTEMBER 12, 2023

Serafim Batzoglou is Chief Data Officer at Seer. Prior to joining Seer, Serafim served as Chief Data Officer at Insitro, leading machine learning and data science in their approach to drug discovery. Seer is leveraging machine learning at all steps from technology development to downstream data analysis.

Machine Learning 299

Machine Learning LLM Data Analysis Data Science 299

Towards AI

MARCH 6, 2025

Was that task truly repetitive, or was it labeled as boring to justify automation? Make no mistake, AI can certainly address many genuine needs across workplaces streamlining data analysis, enabling better customer service, and automating truly repetitive tasks.

AI 57

AI AI Data Analysis AI Tools 57

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

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Organizations can expect to reap the following benefits from implementing OLAP solutions, including the following.

Data Analysis 181

Data Analysis AI AI Automation 181

Pickl AI

FEBRUARY 19, 2025

Summary: The difference between Data Science and Data Analytics lies in their approachData Science uses AI and Machine Learning for predictions, while Data Analytics focuses on analysing past trends. Data Science requires advanced coding, whereas Data Analytics relies on statistical methods.

Data Science 52

Data Science Machine Learning Data Scientist Algorithm 52