Analytics Vidhya

OCTOBER 12, 2024

Introduction Ever wanted to remove an item from a list but not just any item, specifically the one at a certain index? Enter Python pop() method. This built-in function helps you achieve exactly that. It removes an element from a list based on its index and, most importantly, returns the removed element, giving you control […] The post Understanding Python pop() Method appeared first on Analytics Vidhya.

Python 188

Python 188

Marktechpost

OCTOBER 12, 2024

Parameter-efficient fine-tuning (PEFT) methods, like low-rank adaptation (LoRA), allow large pre-trained foundation models to be adapted to downstream tasks using a small percentage (0.1%-10%) of the original trainable weights. A less explored area of PEFT is extending the pre-training phase without supervised labels—specifically, adapting foundation models to new domains using efficient self-supervised pre-training.

AI 126

AI AI ML Computer Vision 126

Analytics Vidhya

OCTOBER 12, 2024

Introduction Chatbots have transformed the way we engage with technology, enabling automated, intelligent conversations across various domains. Building these chat systems can be challenging, especially when aiming for flexibility and scalability. AutoGen simplifies this process by leveraging AI agents, which handle complex dialogues and tasks autonomously.

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Chatbots Automation AI AI 173

Marktechpost

OCTOBER 12, 2024

Retrieval-augmented generation (RAG) is a method that integrates external knowledge sources into large language models (LLMs) to provide accurate and contextually relevant responses. These systems enhance the ability of LLMs to offer detailed and specific answers to user queries by utilizing up-to-date information from various domains. The field is particularly important in applications such as AI-driven question-answering systems, knowledge retrieval platforms, and content creation tools that n

Large Language Models 120

Large Language Models Algorithm ML AI 120

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Analytics Vidhya

OCTOBER 12, 2024

Introduction Data science is a rapidly growing tech field that’s transforming business decision-making. To break into this field, you need the right skills. Fortunately, top institutions like Harvard and IBM offer free online courses. These courses cover everything from basic programming to advanced machine learning. In this article, we’ve listed some of the best free […] The post 19 Free Data Science Courses by Harvard and IBM appeared first on Analytics Vidhya.

Data Science 157

Data Science Machine Learning Python 157

ODSC - Open Data Science

OCTOBER 12, 2024

Editor’s note: Mabel is a speaker for ODSC West this October 29th-31st. Be sure to check out her talk, “ Gen AI in Software Development. What should you be looking for? ,” there! Artificial Intelligence (AI) is not a new concept in the data world. For years, the industry has been developing AI and Machine Learning (ML) models to predict and better understand the data that surrounds us.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Software Development AI 52

Marktechpost

OCTOBER 12, 2024

Machine Learning (ML) models have shown promising results in various coding tasks, but there remains a gap in effectively benchmarking AI agents’ capabilities in ML engineering. Existing coding benchmarks primarily evaluate isolated coding skills without holistically measuring the ability to perform complex ML tasks, such as data preparation, model training, and debugging.

Machine Learning 116

Machine Learning OpenAI ML Engineer ML 116

Marktechpost

OCTOBER 12, 2024

Multimodal Large Language Models (MLLMs) have made significant progress in various applications using the power of Transformer models and their attention mechanisms. However, these models face a critical challenge of inherent biases in their initial parameters, known as modality priors, which can negatively impact output quality. The attention mechanism, which determines how input information is weighted to generate outputs, is especially prone to these biases.

Large Language Models 111

Large Language Models LLM ML Computer Vision 111

Marktechpost

OCTOBER 12, 2024

Large Language Models (LLMs) have gained significant attention in recent years, but improving their performance remains a challenging task. Researchers are striving to enhance already-trained models by creating additional, targeted training data that addresses specific weaknesses. This process, known as instruction tuning and alignment, has shown promise in enhancing model capabilities across various tasks.

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Large Language Models Automation ML Machine Learning 108

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

Generative AI

Marktechpost

OCTOBER 12, 2024

An essential bridge connecting human language and structured query languages (SQL) is text-to-SQL. With its help, users can convert their queries in normal language into SQL commands that a database can comprehend and carry out. This technology makes it easier for users to interface with complex databases, which is especially helpful for those who are not proficient in SQL.

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LLM Machine Learning Data Analysis AI 131

Marktechpost

OCTOBER 12, 2024

LLMs are gaining traction as the workforce across domains is exploring artificial intelligence and automation to plan their operations and make crucial decisions. Generative and Foundational models are thus relied on for multi-step reasoning tasks to achieve planning and execution at par with humans. Although this aspiration is yet to be achieved, we require extensive and exclusive benchmarks to test our models’ intelligence in reasoning and decision-making.

LLM 112

LLM Artificial Intelligence Artificial Intelligence AI 112

Marktechpost

OCTOBER 12, 2024

Large Language Models (LLMs) have gained significant attention for their versatility in various tasks, from natural language processing to complex reasoning. A promising application of these models is the development of autonomous multi-agent systems (MAS), which aim to utilize the collective intelligence of multiple LLM-based agents for collaborative problem-solving.

LLM 117

LLM Natural Language Processing Large Language Models Software Development 117

Marktechpost

OCTOBER 12, 2024

Scaling state-of-the-art models for real-world deployment often requires training different model sizes to adapt to various computing environments. However, training multiple versions independently is computationally expensive and leads to inefficiencies in deployment when intermediate-sized models are optimal. Current solutions like model compression and distillation have limitations, often requiring additional data and retraining, which may degrade model accuracy.

ML 101

ML AI AI Machine Learning 101

Speaker: Brendan Sweeney, VP of Sales & Devyn Blume, Sr. Account Executive

Are you curious about how artificial intelligence is reshaping sales coaching, learning, and development? Join Brendan Sweeney and Devyn Blume of Allego for an engaging new webinar exploring AI's transformative role in sales coaching and performance improvement! Brendan and Devyn will share actionable insights and strategies for integrating AI into coaching and development - ensuring personalized, effective, and scalable training!

AI

Marktechpost

OCTOBER 12, 2024

Ego-centric searches are essential in many applications, from financial fraud detection to social network research, because they concentrate on a single vertex and its immediate neighbors. These queries offer insights into direct connections by analyzing interconnections around a key node. Enabling such searches without jeopardizing privacy becomes a major difficulty when graphs are dispersed over several data sources, especially ones with limited mutual trust.

ML 59

ML AI Tools Artificial Intelligence Artificial Intelligence 59