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Future AI backend processing : Leveraging Flask Python on Firebase Cloud Functions | by Surahutomo Aziz Pradana

Welcome, Firebase enthusiasts! Today, we’re venturing into the realm of serverless computing that can be integrated with AI using Python language to explore the wonders of cloud functions with Python, specifically with Firebase Cloud Functions. These functions offer a seamless way to execute code in response to various triggers, all without the hassle of managing…

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3 Important Considerations in DDPG Reinforcement Algorithm | by Manjeet Singh Nagi | Jun, 2024

Photo by Jeremy Bishop on UnsplashDeep Deterministic Policy Gradient (DDPG) is a Reinforcement learning algorithm for learning continuous actions. You can learn more about it in the video below on YouTube: https://youtu.be/4jh32CvwKYw?si=FPX38GVQ-yKESQKU Here are 3 important considerations you will have to work on while solving a problem with DDPG. Please note that this is not…

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Sentiment Analysis of App Reviews: A Comparison of BERT, spaCy, TextBlob, and NLTK | by Francis Gichere

Kenyan Bank Sentiment Analysis Dashboard — TableauBERT vs spaCy vs TextBlob vs NLTK in Sentiment Analysis for App Reviews Sentiment analysis is the process of identifying and extracting opinions or emotions from text. It is a widely used technique in natural language processing (NLP) with applications in a variety of domains, including customer feedback analysis,…

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Instant AI Model Tuning: Leveraging HNSW Vector with Firebase Genkit for Retrieval-Augmented Generation | by Surahutomo Aziz Pradana | May, 2024

Now let’s practice to learn more how we can build such an AI Solution! Prerequisites Before installing the plugin, ensure you have the following installed: Node.js (version 12 or higher) npm (comes with Node.js) TypeScript (install globally via npm: npm install -g typescript) Genkit (install globally via npm: npm install -g genkit) First thing first,…

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Unlocking the Power of AI: Transforming Data into Actionable Insights | by Marcin Rojek | Apr, 2024

In the ever-evolving landscape of technology, the term “Artificial Intelligence” (AI) has become ubiquitous, often sparking discussions and debates about its true nature and potential. Regardless of the label — whether it’s AI, Artificial Intelligence, Deep Learning, Machine Learning (ML), or automation — these technologies are essentially a collection of algorithms that have the remarkable…

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Energy and Utility Companies are Ready for AI — Let’s Explore the Benefits. | by Marcin Rojek | May, 2024

Explore byteLAKE’s Data Insights: Fueling Efficiency, Sustainability, and Cost Reductions in Energy and Utility Sectors through AI Integration. According to a study in the article, Utilities say they’re ready for AI. Where should they start? (power-grid.com, close to 75% of energy and utility companies have either adopted AI or are actively considering its integration into…

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Simplifying AI: A Dive into Lightweight Fine-Tuning Techniques | by Anurag Lahon

In natural language processing (NLP), fine-tuning large pre-trained language models like BERT has become the standard for achieving state-of-the-art performance on downstream tasks. However, fine-tuning the entire model can be computationally expensive. The extensive resource requirements pose significant challenges. In this project, I explore using a parameter-efficient fine-tuning (PEFT) technique called LoRA to fine-tune BERT…

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System Design in Circadian AI. Navigating Human Biases and Addictions | by Galorian Creations

DALL-E: System Design in Circadian AI: Navigating Human Biases and AddictionsNavigating Human Biases and Addictions In the sequel to “Circadian AI: Harmonizing AGI with Nature’s Rhythms,” we delve deeper into the transformative potential of Artificial General Intelligence (AGI) in enhancing human well-being through advanced system design. Building on the foundation of aligning AGI with natural…

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