Analytics Vidhya

JANUARY 27, 2024

Introduction Pandas is a powerful data manipulation library in Python that provides various data structures, including the DataFrame. A DataFrame is a two-dimensional labeled data structure with columns of potentially different types. It is similar to a table in a relational database or a spreadsheet in Excel. In data analysis, creating a DataFrame is often […] The post 10 Ways to Create Pandas Dataframe appeared first on Analytics Vidhya.

Data Analysis 315

Data Analysis Python Deep Learning Data Science 315

Unite.AI

JANUARY 27, 2024

The University of Amsterdam has marked a significant milestone in the field of chemistry with the introduction of RoboChem, an innovative autonomous chemical synthesis robot. Developed by Professor Timothy Noël's group at the UvA's Van ‘t Hoff Institute for Molecular Sciences, RoboChem stands as a pioneering achievement, demonstrating the potential to dramatically accelerate chemical discovery in pharmaceuticals and various other applications.

Automation 286

Automation Robotics Machine Learning Artificial Intelligence 286

Analytics Vidhya

JANUARY 27, 2024

Introduction Animation has always been a captivating art form, bringing characters and stories to life through the magic of motion. Over the years, technological advancements have revolutionized the animation industry, and now, Generative AI is taking centre stage. Generative AI refers to using artificial intelligence algorithms to create original and unique content.

Generative AI 266

Generative AI Artificial Intelligence Artificial Intelligence Algorithm 266

Marktechpost

JANUARY 27, 2024

The spread of false information is an issue that has persisted in the modern digital era. The lowering of content creation and sharing barriers brought about by the explosion of social media and online news outlets has had the unintended consequence of speeding up the creation and distribution of different forms of disinformation (such as fake news and rumors) and amplifying their impact on a global scale.

LLM 141

LLM Large Language Models Explainability Prompt Engineer 141

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

Towards AI

JANUARY 27, 2024

Last Updated on January 29, 2024 by Editorial Team Author(s): Rakesh M K Originally published on Towards AI. Image created with Microsoft Bing Image Maker AutoKeras AutoKeras is Python’s Keras-based AutoML library for developing Deep Learning models. Built on top of TensorFlow by DATA Lab at Texas A&M University, it offers a solutions for classification, regression, time series forecasting, and much more.

Deep Learning 93

Deep Learning Explainability ML Engineer Data Scientist 93

Towards AI

JANUARY 27, 2024

Last Updated on January 29, 2024 by Editorial Team Author(s): Afaque Umer Originally published on Towards AI. Unlocking the Power of Compose for Seamless Machine Learning WorkflowsPhoto by Larisa Birta on Unsplash In the ever-evolving landscape of machine learning experimentation and application development, navigating the coordination of diverse system components poses a significant logistical challenge.

Machine Learning 85

Machine Learning Data Scientist Data Science AI 85

Marktechpost

JANUARY 27, 2024

In language model alignment, the effectiveness of reinforcement learning from human feedback (RLHF) hinges on the excellence of the underlying reward model. A pivotal concern is ensuring the high quality of this reward model, as it significantly influences the success of RLHF applications. The challenge lies in developing a reward model that accurately reflects human preferences, a critical factor in achieving optimal performance and alignment in language models.

AI Strategy 132

AI Strategy Large Language Models AI AI 132

Bugra Akyildiz

JANUARY 27, 2024

Articles One of the readers of the newsletter sent me the following blog post about modular deep learning and it is very interesting research direction for foundational models. It stars with the following problems to solve for the existing traditional Foundation Models: Monolithic Bottlenecks: Traditional deep learning models are built as intricate, interconnected webs.

Deep Learning 59

Deep Learning Convolutional Neural Networks Large Language Models LLM 59

Marktechpost

JANUARY 27, 2024

Developing foundation models like Large Language Models (LLMs), Vision Transformers (ViTs), and multimodal models marks a significant milestone. These models, known for their versatility and adaptability, are reshaping the approach towards AI applications. However, the growth of these models is accompanied by a considerable increase in resource demands, making their development and deployment a resource-intensive task.

Machine Learning 131

Machine Learning Large Language Models Computer Vision Algorithm 131

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Marktechpost

JANUARY 27, 2024

Large-scale multilingual language models are the foundation of many cross-lingual and non-English Natural Language Processing (NLP) applications. These models are trained on massive volumes of text in multiple languages. However, the drawback to their widespread use is that because numerous languages are modeled in a single model, there is competition for the limited capacity of the model.

Natural Language Processing 131

Natural Language Processing Artificial Intelligence Artificial Intelligence NLP 131

Marktechpost

JANUARY 27, 2024

There is a need to build systems that can respond to user inputs, remember past interactions, and make decisions based on that history. This requirement is crucial for creating applications that behave more like intelligent agents, capable of maintaining a conversation, remembering past context, and making informed decisions. Currently, some solutions address parts of this problem.

AI 126

AI AI Artificial Intelligence Artificial Intelligence 126

Marktechpost

JANUARY 27, 2024

With the growth of trending AI applications, Machine Learning ML models are being used for various purposes, leading to an increase in the advent of multimodal models. Multimodal models are very useful, and researchers are putting a lot of emphasis on these nowadays as they help mirror the complexity of human cognition by integrating diverse data sources such as text and images.

Conversational AI 114

Conversational AI AI AI AI Research 114