Analytics Vidhya

MAY 15, 2023

Microsoft AI Research has recently introduced a new framework called Automatic Prompt Optimization (APO) to significantly improve the performance of large language models (LLMs). This framework is designed to help users create better prompts with minimal manual intervention & optimize prompt engineering for better results.

Optimization 275

Optimization Modeling Analytics 275

Analytics Vidhya

SEPTEMBER 11, 2023

It will be engineered to optimize decision-making and enhance performance in real-world complex systems. Introduction Reinforcement Learning from Human Factors/feedback (RLHF) is an emerging field that combines the principles of RL plus human feedback.

Optimization 308

Optimization Strategy Data-driven Interactive 308

Analytics Vidhya

JANUARY 15, 2024

In the dynamic realm of language model development, a recent groundbreaking paper titled “Direct Preference Optimization (DPO)” by Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Chris Manning, and Chelsea Finn, has captured the attention of AI luminaries like Andrew Ng.

Optimization 266

Optimization Modeling Analytics IT 266

Analytics Vidhya

NOVEMBER 30, 2023

In a development, Amazon Bedrock introduces the ability to assess, compare, and choose the optimal foundation models (FMs) tailored to your specific need. The Model Evaluation feature, now in preview, empowers developers with a range of evaluation tools, offering both automatic and human benchmarking options.

Modeling 265

Modeling Optimization Analytics 265

Analytics Vidhya

SEPTEMBER 21, 2023

Introduction Large language models (LLMs) are prominent innovation pillars in the ever-evolving landscape of artificial intelligence. These models, like GPT-3, have showcased impressive natural language processing and content generation capabilities.

Modeling 283

Modeling Optimization Analytics 283

Analytics Vidhya

OCTOBER 7, 2021

A deep learning model consists of activation function, input, output, hidden layers, loss function, etc. Any deep learning model tries to […]. The post A Comprehensive Guide on Deep Learning Optimizers appeared first on Analytics Vidhya.

Deep Learning 301

Deep Learning Optimization Machine Learning Data Science 301

Analytics Vidhya

DECEMBER 24, 2021

The post ML Hyperparameter Optimization App using Streamlit appeared first on Analytics Vidhya. It was designed especially for Machine Learning and Data Scientist team. Using Streamlit, we can quickly create interactive web apps and deploy them. Frontend […].

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Optimization Machine Learning Interactive Data Science 366

Analytics Vidhya

OCTOBER 30, 2023

The most challenging part of integrating AI into an application is […] The post Mastering AI Optimization and Deployment with Intel’s OpenVINO Toolkit appeared first on Analytics Vidhya. Enterprises and businesses believe in integrating reliable and responsible AI in their application to generate more revenue.

Optimization 302

Optimization Software Enterprise Analytics 302

Analytics Vidhya

JANUARY 29, 2024

But, here’s the problem: this encyclopedia is huge and requires significant time and effort […] The post Optimizing Neural Networks: Unveiling the Power of Quantization Techniques appeared first on Analytics Vidhya. Now, this friend has a precise way of doing things, like he has a dictionary in his head.

Optimization 251

Optimization Analytics IoT Deep Learning 251

Analytics Vidhya

SEPTEMBER 29, 2021

This article was published as a part of the Data Science Blogathon Dear readers, In this blog, we will build a random forest classifier(RFClassifier) model to detect breast cancer using this dataset from Kaggle. The post A Hands-On Discussion on Hyperparameter Optimization Techniques appeared first on Analytics Vidhya.

Optimization 262

Optimization Data Science Publishing Modeling 262

Analytics Vidhya

AUGUST 23, 2021

This article was published as a part of the Data Science Blogathon Building a simple Machine Learning model using Pytorch from scratch. Image by my great learning Introduction Gradient descent is an optimization algorithm that is used to train machine learning models and is now used in a neural network.

Machine Learning 398

Machine Learning Modeling Data Science Optimization 398

Analytics Vidhya

JUNE 1, 2023

With franchise leagues like IPL and BBL, teams rely on statistical models and tools for competitive edge. This article explores how data analytics optimizes strategies by leveraging player performances and opposition weaknesses. Introduction Cricket embraces data analytics for strategic advantage.

Predictive Modeling 261

Predictive Modeling Modeling Statistics Optimization 261

Analytics Vidhya

AUGUST 26, 2023

In this article, we will explore how PEFT methods optimize the adaptation of Large Language Models (LLMs) to specific tasks. We will unravel the advantages and disadvantages of PEFT, […] The post Parameter-Efficient Fine-Tuning of Large Language Models with LoRA and QLoRA appeared first on Analytics Vidhya.

Modeling 227

Modeling Optimization Analytics IT 227

Analytics Vidhya

NOVEMBER 30, 2021

This article was published as a part of the Data Science Blogathon A comprehensive guide for finding the best hyper-parameter for your model efficiently. Tuning hyperparameter is more efficient with Bayesian optimized algorithms compared to Brute-force algorithms. Introduction Optimizing ML models […].

Modeling 301

Modeling Optimization Data Science Publishing 301

Smart Data Collective

FEBRUARY 3, 2022

Therefore, the subscription business model is changing how customers pay for the service they receive. Hover, the subscription model can be quite challenging for businesses. If they wish to implement this model, they need to have an information collection system to keep track of billing and customer requests.

Optimization 109

Optimization Data Analytics Modeling Analytics 109

CIO Business Intelligence

OCTOBER 2, 2023

As long as you remain aware of potential risk factors and take action to mitigate potential risk, there should be no reason you cannot certify out of your ULA and move toward alternative options such as Rimini Street to identify tangible cost savings and optimize your Return on Investment (ROI).

ROI 90

ROI Optimization Enterprise Modeling 90

Analytics Vidhya

MAY 15, 2022

In order to develop any deep learning model, one must decide on the most optimal values of […]. The post Impact of Hyperparameters on a Deep Learning Model appeared first on Analytics Vidhya.

Deep Learning 254

Deep Learning Modeling Data Science Optimization 254

IBM Big Data Hub

MAY 17, 2024

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

Modeling 82

Modeling Cost-Benefit Optimization Digital Transformation 82

Analytics Vidhya

OCTOBER 7, 2021

This article was published as a part of the Data Science Blogathon Overview of Model Deployment Using Heroku Image 1 One of the most prevalent misunderstandings and mistakes for a failed ML project is spending a significant amount of time optimizing the ML model.

Machine Learning 279

Machine Learning Modeling Data Science Optimization 279

IBM Big Data Hub

FEBRUARY 5, 2024

Every asset manager, regardless of the organization’s size, faces similar mandates: streamline maintenance planning, enhance asset or equipment reliability and optimize workflows to improve quality and productivity. These foundation models, built on large language models, are trained on vast amounts of unstructured and external data.

Optimization 99

Optimization Management Key Performance Indicator Modeling 99

Analytics Vidhya

APRIL 26, 2022

The post How to Optimize ROI Using Customer Lifetime Value? More customers translate into higher revenues and better profitability in the long run. But in recent times, and due to heavy competition customer loyalty to a brand has […]. appeared first on Analytics Vidhya.

ROI 245

ROI Optimization Data Science Publishing 245

Dataiku

JUNE 22, 2022

ML outcome optimization is the process of finding optimal feature values that give the model prediction minimum (or maximum) over a defined space. For black-box ML models, we cannot assume any of the usual smoothness properties for optimization, such as convexity or even differentiability.

Optimization 59

Optimization Modeling IT 59

KDnuggets

OCTOBER 19, 2023

Gradient descent is an optimization technique used to minimise errors in machine learning models. By iteratively adjusting parameters in the steepest direction of decrease, it seeks the lowest error value.

Optimization 120

Optimization Machine Learning Modeling IT 120

CIO Business Intelligence

OCTOBER 16, 2023

Going back after the fact to optimize for cost while you’re still trying to operate and grow can make things even harder.” By quickly showing engineers the financial implications of feature development and product changes, for example, they can optimize features for cost in the same way they tune for performance or uptime.

Optimization 133

Optimization Enterprise Finance Data Processing 133

KDnuggets

APRIL 6, 2022

Using AIMET, developers can incorporate advanced model compression and quantization algorithms into their PyTorch and TensorFlow model-building pipelines for automated post-training optimization, as well as for model fine-tuning.

Optimization 112

Optimization Modeling 112

Cloudera

DECEMBER 19, 2023

There, I met with IT leaders across multiple lines of business and agencies in the US Federal government focused on optimizing the value of AI in the public sector. As also expected, most had experimented on their own with large language models (LLM) and image generators. Our government leaders had several suggestions: Start small.

Optimization 86

Optimization Cost-Benefit Unstructured Data Risk 86

Analytics Vidhya

MAY 7, 2024

However, inaccurate retrieval can lead to sub-optimal responses. Cohere’s re-ranker model enhances this process by evaluating and ordering search results based on contextual relevance, improving accuracy and saving time for specific information seekers.

Optimization 268

Optimization Modeling Analytics 268

IBM Big Data Hub

JULY 5, 2023

However, cloud services costs can be higher than anticipated, so monitoring and optimizing your cloud spend is critical. Cloud cost optimization combines strategies, techniques, best practices and tools to help reduce cloud costs, find the most cost-effective way to run your applications in the cloud environment, and maximize business value.

Optimization 70

Optimization Forecasting ROI Metrics 70

IBM Big Data Hub

OCTOBER 17, 2023

For example, say we predict the quality of the clinker in advance, then we are able to optimize the heat energy and combustion in the cement kiln in such a way that quality clinker is produced at minimum energy. Such optimization of the processes reduces energy consumption and in turn reduces both energy emission and process emission.

Modeling 106

Modeling Optimization Manufacturing Forecasting 106

IBM Big Data Hub

MARCH 21, 2024

In this blog, we’ll explore seven key strategies to optimize infrastructure for AI workloads, empowering organizations to harness the full potential of AI technologies. High-performance computing systems Investing in high-performance computing systems tailored for AI accelerates model training and inference tasks.

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Optimization Software Data-driven Consulting 68