IBM Journey to AI blog

AUGUST 11, 2023

MLOps, which stands for machine learning operations, uses automation, continuous integration and continuous delivery/deployment (CI/CD) , and machine learning models to streamline the deployment, monitoring and maintenance of the overall machine learning system. How to use ML to automate the refining process into a cyclical ML process.

Data Science 144

Data Science DevOps Machine Learning Data Scientist 144

Heartbeat

FEBRUARY 1, 2023

MLOps is a highly collaborative effort that aims to manipulate, automate, and generate knowledge through machine learning. The machine learning engineers are in charge of taking the models developed by data scientists and deploying them into production. They may also be involved in the deployment process’s automation.

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

ODSC - Open Data Science

SEPTEMBER 19, 2023

Prompt engineers take on this challenge by optimizing LLMs to process and generate content at scale. This task involves a combination of software engineering expertise and computational efficiency. Engineers delve into the architecture of LLMs, identifying potential bottlenecks and areas for improvement.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Large Language Models Software Engineer 98

ODSC - Open Data Science

JUNE 3, 2023

With an AI coding assistant, syntax becomes easier to remember as these programs can help you correct your mistakes, but most importantly, explain why a certain script that is coming up wrong is wrong. Software Engineers This wouldn’t be a proper blog if we didn’t touch the elephant in the room -software engineers.

Data Scientist 52

Data Scientist Software Engineer Data Science AI 52

Robot Writers AI

DECEMBER 17, 2023

“For instance, the video’s YouTube description explains that ‘for the purposes of this demo, latency has been reduced and Gemini outputs have been shortened for brevity.’ Observes Blake: “Google modified interactions with Gemini in numerous ways in order to create the demonstration.

AI 100

AI AI ChatGPT Robotics 100

ODSC - Open Data Science

DECEMBER 19, 2023

They need to be able to explain complex technical concepts to non-technical stakeholders and to identify and solve problems that arise during the development and implementation of AI models. Machine Learning Engineer Machine learning engineers are responsible for developing and deploying machine learning models.

AI Product Manager 96

AI Product Manager AI Product Management Prompt Engineer Prompt Engineering 96

DataRobot Blog

MAY 31, 2022

For example, a job description for a software engineer in the private sector was only one paragraph long, while the government job description was seven pages long. DataRobot automatically provides explainable insights such as prediction explanations to help leaders understand “why” a specific prediction is made.

AI 59

AI AI Software Engineer Explainability 59

IBM Journey to AI blog

JULY 6, 2023

A major online media company uses data science to develop personalized content, enhance marketing through targeted ads and continuously update music streams, among other automation decisions. The company made its data open-source, and trains and empowers employees to take advantage of data-driven insights.

Data Science 148

Data Science Machine Learning Big Data Data Mining 148

Towards AI

JANUARY 27, 2023

I started my journey as a software engineer around technologies such as web stack including python, javascript, and java stack. Later we went to automate this to complete Business Intelligence and Reporting tool having aggregated and detailed charts. But I didn’t about data science in a way on how it is known.

Data Analysis 78

Data Analysis Data Science Software Engineer Business Intelligence 78

ODSC - Open Data Science

OCTOBER 20, 2023

The Tangent Information Modeler, Time Series Modeling Reinvented Philip Wauters | Customer Success Manager and Value Engineer | Tangent Works Existing techniques for modeling time series data face limitations in scalability, agility, explainability, and accuracy.

NLP 52

NLP Data Science Machine Learning Data Analysis 52

AWS Machine Learning Blog

FEBRUARY 6, 2023

We end by explaining how contact centers can keep AI models up to date using Talkdesk AI Trainer. Solution overview The solution consists of the following key components: Amazon Lex – Amazon Lex combines with Amazon Polly to automate customer service interactions by adding conversational AI capabilities to your contact center.

Conversational AI 67

Conversational AI Chatbots Automation Natural Language Processing 67

John Snow Labs

MAY 15, 2023

Explainability and Interpretability: Models should be capable of answer stakeholder questions about the decision-making processes of AI systems. Therefore, a well-engineered production system should work reliably on common inputs and be safe & robust when handling uncommon ones.

NLP 52

NLP Software Engineer Data Scientist Responsible AI 52

deepsense.ai

OCTOBER 8, 2023

We compare the existing solutions and explain how they work behind the scenes. We can define an AI Agent as a computer program or system that can perceive its environment, process information, and make decisions or take actions to achieve specific goals (such as solving software engineering problems). Back to point 2.

Auto-complete 92

Auto-complete LLM AI AI 92

Flipboard

NOVEMBER 21, 2023

MATLAB   is a popular programming tool for a wide range of applications, such as data processing, parallel computing, automation, simulation, machine learning, and artificial intelligence. He creates solutions that enable engineers and scientists to harness the full potential of MATLAB and Simulink in cloud-based environments.

Machine Learning 116

Machine Learning Auto-classification Python Algorithm 116

AWS Machine Learning Blog

FEBRUARY 29, 2024

This post explains how to integrate the Amazon Personalize Search Ranking plugin with OpenSearch Service to enable personalized search experiences. Deploy the CloudFormation stack The CloudFormation stack automates the deployment of the OpenSearch Service domain and SageMaker Notebook instance.

Auto-complete 89

Auto-complete AI AI ML 89

Unite.AI

APRIL 22, 2024

His interests fall in multiple areas, such as Artificial Intelligence, Software Engineering, and High Performance Computing. This allows the engineering teams to focus on the business logic, while our AI-Service handles the complexities of dealing with different AI providers. He has a PhD.

Software Engineer 147

Software Engineer AI Modeling Generative AI Large Language Models 147

The MLOps Blog

JANUARY 23, 2023

Not a fork: – The MLOps team should consist of a DevOps engineer, a backend software engineer, a data scientist, + regular software folks. I don’t see what special role ML and MLOps engineers would play here. – We need both automated continuous monitoring AND periodic manual inspection. Ok, let me explain.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

Unite.AI

FEBRUARY 21, 2024

Could you share your personal story of how you became involved with software engineering, and worked your way up to being CTO of Astronomer? For me, engineering has always been a great creative outlet: I can come up with an idea and use whatever technology’s necessary to build towards a vision.

LLM 147

LLM Data Platform Software Engineer Chatbots 147

ODSC - Open Data Science

JULY 7, 2023

Most of the discussions have focused on the implications for writers, designers, software engineers, researchers, lawyers, and administrative workers. This involves building relationships, explaining concepts, and clear communication with others — particularly non-data specialists. But the use of AI could go further.

Explainability 59

Explainability AI AI Data Science 59

Flipboard

AUGUST 1, 2023

I used to be a software engineer, so I’m a little rusty on coding. ” Boaz Ashkenazy, founder and CEO of Simply Augmented , a Seattle startup that helps brands leverage generative AI and software automation. And it’s a little bit easier to explain.” “I just founded this company.

Generative AI 106

Generative AI Software Engineer AI AI 106

Flipboard

MARCH 14, 2023

An image autogenerated by Midjourney , a text-to-image tool, when given the prompt “people performing office tasks with AI, collage art.” | Midjourney How Ethan and Lilach Mollick learned to stop worrying and start automating their jobs. Now, however, we have tools with the potential to automate a significant portion of our jobs.

ChatGPT 123

ChatGPT AI AI Automation 123

O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Software Architecture. The new category is often called MLOps.

DevOps 138

DevOps Software Engineer Data Scientist ML 138

AWS Machine Learning Blog

SEPTEMBER 14, 2023

The following section explains how the workflow can be used in different industries and verticals. Specific use case: Automate issue resolution for employees based on corporate guidelines. Specific use case: Use customer financial history and previous loan applications to decide and explain loan decision.

Generative AI 93

Generative AI LLM Large Language Models Software Engineer 93

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

Flipboard

JULY 31, 2023

Nowadays, with the advent of deep learning and convolutional neural networks, this process can be automated, allowing the model to learn the most relevant features directly from the data. In the early days of machine learning, this was often done manually, with researchers defining features (e.g., edges, corners, or color histograms).

Machine Learning 104

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 104

AWS Machine Learning Blog

DECEMBER 14, 2023

The flexible and extensible interface of SageMaker Studio allows you to effortlessly configure and arrange ML workflows, and you can use the AI-powered inline coding companion to quickly author, debug, explain, and test code. Majisha Namath Parambath is a Senior Software Engineer at Amazon SageMaker.

Generative AI 97

Generative AI AI Tools ML AI 97

ODSC - Open Data Science

JANUARY 25, 2023

To make sure that machine learning solutions are fair and the value of their predictions easy to understand and explain, it is essential to get access to tools that developers and data scientists can use to improve accuracy and asses their models’ fairness and mitigate any observed unfairness issues.

Machine Learning 59

Machine Learning Data Scientist ML Python 59

Artificial Corner

AUGUST 3, 2023

Examples: *Create me a plan for a vacation roadtrip for me and my family* *Explain the relativity theory to me* *Summarize the following text…* *Implement me a snake game in Python* *Tell me what is the sense of life* What is prompt engineering? Previously, we had copy/paste engineers navigating the seas of Google or StackOverflow.

Prompt Engineer 98

Prompt Engineer Prompt Engineering Large Language Models LLM 98

AWS Machine Learning Blog

APRIL 26, 2023

Commonly, the work is split up between the following workstreams: Cloud engineering (infrastructure and security) – Focuses on verifying that the AWS accounts and infrastructure are set up and secure ahead of EBA. Data engineering – Identifies the data sources, sets up data ingestion and pipelines, and prepares data using Data Wrangler.

ML 88

ML Machine Learning Data Science Data Drift 88

The MLOps Blog

FEBRUARY 27, 2023

Michal, to warm you up for all this question-answering, how would you explain to us managing computer vision projects in one minute? What I mean is when data scientists are working hand in hand with software engineers or MLOps engineers, that would then take over or wrap up the solution. Any closing thoughts on that?

Computer Vision 52

Computer Vision Auto-classification Auto-complete ML 52

Chatbots Life

MAY 13, 2023

Ask you interview questions for a specific job I'm interviewing for a software engineer position, can you give me some interview questions Please provide me with some common interview questions for a marketing manager role Give you gift ideas for business partners, customers, or clients I need gift ideas for my clients, can you help?

ChatGPT 95

ChatGPT Chatbots Explainability Software Engineer 95

AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. Amazon SageMaker provides purpose-built tools for ML teams to automate and standardize processes across the ML lifecycle. Neelam Koshiya is an Enterprise Solutions Architect at AWS.

Machine Learning 86

Machine Learning Python ML Automation 86

ODSC - Open Data Science

FEBRUARY 8, 2024

A data product may aim to automate a decision, or it may aim to assist a human decision-maker. This could include a variety of job titles like software engineer, machine learning engineer, applied scientist, etc. Data science — The discipline within the organization that makes data products.

AI Strategy 52

AI Strategy Data Scientist Data Science AI 52

The MLOps Blog

OCTOBER 3, 2023

I started from tech, my first job was an internship at Google as a software engineer. I’m from Poland, and I remember when I got an offer from Google to join as a regular software engineer. You can explain, “Hey, this is the logic of the function, this is what the terms mean, etc. How awful are they?”

ML 52

ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

AUGUST 29, 2023

In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification by using Amazon SageMaker , Amazon EventBridge , AWS Lambda , Amazon Simple Notification Service (Amazon SNS), HashiCorp Terraform, and GitLab CI/CD.

Data Scientist 72

Data Scientist Data Quality Python ML 72

AWS Machine Learning Blog

NOVEMBER 22, 2023

Generative AI can automate these tasks through autonomous agents. Swagata Prateek is a Senior Software Engineer working in Amazon Location Service at Amazon Web Services (AWS) where he focuses on Generative AI and geospatial. mean(), longitude=airbnb_gdf['longitude'].mean(),

Generative AI 92

Generative AI Python Data Scientist Large Language Models 92

AWS Machine Learning Blog

FEBRUARY 10, 2023

There is a need for an automated coverage classification model that can scale effectively and efficiently to reduce cost and turnaround time. We describe how we designed an accurate, explainable ML model to make coverage classification from player tracking data, followed by our quantitative evaluation and model explanation results.

Computer Vision 65

Computer Vision Machine Learning ML Convolutional Neural Networks 65