IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 225

Machine Learning Automation AI AI 225

IBM Journey to AI blog

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content.

Large Language Models 289

Large Language Models LLM Explainability Chatbots 289

IBM Journey to AI blog

DECEMBER 20, 2023

A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters. With IBM® watsonx.ai ™ AI studio, developers can manage ML algorithms and processes with ease.

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

IBM Journey to AI blog

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Learn more about harnessing the power of generative AI for your business by exploring IBM watsonx , the AI and data platform built for business.

Generative AI 343

Generative AI AI AI Chatbots 343

IBM Journey to AI blog

JULY 17, 2023

Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. is a studio to train, validate, tune and deploy machine learning (ML) and foundation models for Generative AI. Watsonx.ai

Generative AI 171

Generative AI Auto-complete Automation AI 171

IBM Journey to AI blog

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. The platform comprises three powerful products: The watsonx.ai That’s where the foundation model enters the picture.

Generative AI 176

Generative AI Data Scientist Machine Learning BERT 176

Flipboard

NOVEMBER 24, 2023

Data scientists and ML engineers require capable tooling and sufficient compute for their work. Therefore, BMW established a centralized ML/deep learning infrastructure on premises several years ago and continuously upgraded it. Joaquin Rinaudo is a Principal Security Architect at AWS ProServe.

ML 152

ML DevOps Data Scientist ML Engineer 152

IBM Journey to AI blog

APRIL 18, 2024

Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move. Most importantly, no matter the strength of AI (weak or strong), data scientists, AI engineers, computer scientists and ML specialists are essential for developing and deploying these systems.

Neural Network 256

Neural Network LLM Algorithm NLP 256

Marktechpost

JULY 17, 2023

Predictive analytics can make use of both structured and unstructured data insights. What Relationship Exists Between Predictive Analytics, Deep Learning, and Artificial Intelligence? For machine learning to identify common patterns, large datasets must be processed. In this article, some of them are described.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

ODSC - Open Data Science

SEPTEMBER 17, 2024

LightGBM’s ability to handle large-scale data with lightning speed makes it a valuable tool for engineers working with high-dimensional data. Caffe Caffe is a deep learning framework focused on speed, modularity, and expression. It’s particularly popular for image classification and convolutional neural networks CNNs.

Software Engineer 52

Software Engineer Neural Network Deep Learning Convolutional Neural Networks 52

TheSequence

JUNE 18, 2023

. 📝 Editorial: Yann LeCun's Vision Starts Materializing With all the hype surrounding generative AI, we sometimes overlook the thrilling advancements in other areas of the deep learning ecosystem. OctoML launched OctoAI , a platform for running, tuning and scaling generative AI models.

Computer Vision 98

Computer Vision Generative AI ML Large Language Models 98

AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud.

Data Extraction 118

Data Extraction Data Ingestion ML Machine Learning 118

AWS Machine Learning Blog

FEBRUARY 13, 2024

With a strong background in computer vision, data science, and deep learning, he holds a postgraduate degree from IIT Bombay. He has worked on building enterprise-grade applications, building data platforms in multiple organizations and reporting platforms to streamline decisions backed by data.

Computer Vision 118

Computer Vision Convolutional Neural Networks ML AI 118

Heartbeat

DECEMBER 7, 2023

Quality and Consistency: Data products must be built using standardized data models, definitions, and requirements and rigorously tested to ensure quality, reliability, and interoperability. ? Collaboration: Self-service data platforms should facilitate collaboration and knowledge sharing across different teams and domains.

Metadata 52

Metadata Data Platform Deep Learning Data Quality 52

The MLOps Blog

JANUARY 26, 2024

Keeping track of how exactly the incoming data (the feature pipeline’s input) has to be transformed and ensuring that each model receives the features precisely how it saw them during training is one of the hardest parts of architecting ML systems. This is where feature stores come in. The ML systems mostly follow the same structure.

Machine Learning 72

Machine Learning Metadata ML Python 72

AWS Machine Learning Blog

SEPTEMBER 18, 2023

The results of SUEWS are then visualized, in this case with Arup’s existing geospatial data platform. Mark provides expertise in earth observation and geospatial data analysis to a broad range of clients and delivers insights and thought leadership using both traditional machine learning and deep learning techniques.

Data Scientist 110

Data Scientist ML Machine Learning ML Engineer 110

Marktechpost

JULY 17, 2023

To educate self-driving cars on how to avoid killing people, the business concentrates on some of the most challenging use cases for its synthetic data platform. Its most recent development, made in partnership with the Toyota Research Institute, teaches autonomous systems about object permanence using synthetic data.

Machine Learning 52

Machine Learning Data Scientist Computer Vision Deep Learning 52

AWS Machine Learning Blog

AUGUST 3, 2023

Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning. Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. We use deep learning models to solve this problem.

Computer Vision 70

Computer Vision Data Scientist ML Deep Learning 70

AWS Machine Learning Blog

MARCH 29, 2023

Conclusion HAYAT HOLDING was evaluating an advanced analytics platform as part of their digital transformation strategy and wanted to bring AI to the organization for quality prediction in production. HAYAT KIMYA integrated the ML solution in one of its plants. Hayat” means “life” in Turkish.

ML 85

ML Machine Learning Algorithm Data Scientist 85

Snorkel AI

FEBRUARY 13, 2023

And then finally, we also work on machine learning and AI for the Customer Experience, where we’re building “smart assistants” to help our customers, agents, and technicians solve different kinds of problems. One way you can train it is by using synthetic examples. At the same time, this is not exhaustive, right?

Metadata 52

Metadata Machine Learning Deep Learning BERT 52

Snorkel AI

FEBRUARY 13, 2023

And then finally, we also work on machine learning and AI for the Customer Experience, where we’re building “smart assistants” to help our customers, agents, and technicians solve different kinds of problems. One way you can train it is by using synthetic examples. At the same time, this is not exhaustive, right?

Metadata 52

Metadata Machine Learning Deep Learning BERT 52

John Snow Labs

AUGUST 7, 2024

Gen AI, particularly through deep learning models, has shown remarkable accuracy in diagnosing diseases from medical images. Healthcare data is sensitive, and its handling must comply with strict regulations like HIPAA in the United States. This lack of interpretability and transparency can hinder trust and adoption.

Generative AI 59

Generative AI AI AI Algorithm 59

Pickl AI

APRIL 26, 2024

Yes, I am proficient in data visualisation tools such as Tableau, Power BI, and Matplotlib in Python, which I use to create interactive and insightful visualisations for data analysis. Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure?

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

ODSC - Open Data Science

JULY 19, 2023

Data Estate: This element represents the organizational data estate, potential data sources, and targets for a data science project. Data Engineers would be the primary owners of this element of the MLOps v2 lifecycle. The Azure data platforms in this diagram are neither exhaustive nor prescriptive.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

Pickl AI

DECEMBER 4, 2023

Implementing robust data validation processes. Clinical Research Acceleration Speeds up research processes and drug development Integrating diverse data sources. Implementing interoperable data platforms. 9,43,649 Business acumen, Data Visualisation tools (e.g., 10,00000 Deep learning, programming (e.g.,

Data Analysis 52

Data Analysis Data Quality Artificial Intelligence Artificial Intelligence 52

AWS Machine Learning Blog

SEPTEMBER 6, 2024

Rahul Jani is a Data Architect with AWS Professional Services. He collaborates closely with enterprise customers building modern data platforms, generative AI applications, and MLOps. He is specialized in the design and implementation of big data and analytical applications on the AWS platform.

Generative AI 87

Generative AI LLM AI AI 87

John Snow Labs

FEBRUARY 29, 2024

Gen AI, particularly through deep learning models, has shown remarkable accuracy in diagnosing diseases from medical images. Healthcare data is sensitive, and its handling must comply with strict regulations like HIPAA in the United States. This lack of interpretability and transparency can hinder trust and adoption.

Generative AI 40

Generative AI AI AI Algorithm 40

The MLOps Blog

MARCH 12, 2024

Tools range from data platforms to vector databases, embedding providers, fine-tuning platforms, prompt engineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. However, transforming raw LLMs into production-ready applications presents complex challenges.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models LLM 52

The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. As you’ve been running the ML data platform team, how do you do that? Stefan: Yeah. Thanks for having me.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

OCTOBER 3, 2023

What helped me both in the transition to the data scientist role and then also to the MLOps engineer role was doing a combination of boot camps, and when I was going to the MLOps engineer role, I also took this one workshop that’s pretty well-known called Full Stack Deep Learning. I really enjoyed it. How was my code?”

ML 52

ML Data Scientist Machine Learning Data Science 52

ODSC - Open Data Science

MARCH 18, 2025

Jon Krohn, Host of the SuperDataScience Podcast Jon Krohn is a leading voice in data science as the host of SuperDataScience, the industrys most-listened-to podcast. A prolific researcher with over 20 published papers, 1,000+ citations, and 20 patents, his expertise spans deep learning, interpretability, and sports analytics.

Data Science 64

Data Science Machine Learning Software Engineer Data Scientist 64

AWS Machine Learning Blog

AUGUST 6, 2024

Originating from advancements in artificial intelligence (AI) and deep learning, these models are designed to understand and translate descriptive text into coherent, aesthetically pleasing music. Obtain the AWS Deep Learning Containers for Large Model Inference from pre-built HuggingFace Inference Containers.

Auto-complete 88

Auto-complete Metadata Generative AI Deep Learning 88

Marktechpost

NOVEMBER 1, 2024

PyTorch The deep learning framework PyTorch is well-known for its adaptability and broad support for applications like computer vision, reinforcement learning, and natural language processing. Deep learning practitioners choose it because of its large community and libraries.

Artificial Intelligence 96

Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 96

The MLOps Blog

MARCH 21, 2023

They work with other users to make sure the data reflects the business problem, the experimentation process is good enough for the business, and the results reflect what would be valuable to the business. Name Short Description Algorithmia Securely govern your machine learning operations with a healthy ML lifecycle. Allegro.io

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

TransOrg Analytics

SEPTEMBER 24, 2024

Google Data Studio: Turn data into informative dashboards and reports. Data & ML/LLM Ops on GCP Vertex AI: End-to-end platform to build, deploy, and scale ML models. TensorFlow Enterprise: High-performance deep learning on Google Cloud.

ETL 52

ETL LLM Data Ingestion Automation 52

TransOrg Analytics

SEPTEMBER 24, 2024

Google Data Studio: Turn data into informative dashboards and reports. Data & ML/LLM Ops on GCP Vertex AI: End-to-end platform to build, deploy, and scale ML models. TensorFlow Enterprise: High-performance deep learning on Google Cloud.

ETL 52

ETL LLM Data Ingestion Automation 52

AWS Machine Learning Blog

DECEMBER 11, 2024

The bot is expected to act as a virtual assistant to answer common questions, identify and solve issues, monitor platform health, and provide best practice suggestions, all aimed at helping Tealium customers get the most value from their customer data platform. This was achieved by building an: Evaluation pipeline.

Generative AI 67

Generative AI Chatbots Prompt Engineer Prompt Engineering 67