#NLP, or Natural Language Processing, is undoubtedly one of the most captivating domains I have ventured into! The ability to establish a connection between speech, writing, and computer science is truly astonishing. In our latest journal publication at Synapse Journal, I delved into the realm of NLP, aiming to delve deeper into this enigmatic world. Furthermore, in addition to reading this article, you can access the corresponding code on my #Kaggle account through the provided link: https://lnkd.in/dASY5Vqk
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🖥️Excited to share my latest article on Medium: "Unlocking the Secrets of Natural Language Processing: A Beginner's Guide!" In this post, I explore the fundamentals of NLP, its importance in today's digital landscape, and key concepts like text preprocessing, representation, and various techniques. Whether you’re new to AI or looking to deepen your understanding, this guide is for you! 🔗 Read the full article here https://lnkd.in/dpaATWub Let’s embark on this NLP journey together! I’d love to hear your thoughts and questions in the comments. #NLP #ArtificialIntelligence #MachineLearning #NaturalLanguageProcessing #TechForGood
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🎯 Just published a new blog on Medium! Hey fellas 👋 , tried something different and just wrote a blog on Medium, In my latest article, I dive into Natural Language Processing and try to build a preamble. Take a moment to explore my thoughts and join the conversation. I’d love to hear your feedback! 🔗 Read it here: https://lnkd.in/dzyZ97eD #Innovation #IndustryTrends #NLP #BlogPost
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🚀 Excited to share my latest project: an NLP Title Generator! Using natural language processing, this tool automatically generates titles from input text, demonstrating the power of neural networks in recognizing patterns and summarizing content. This project reflects my passion for NLP and my desire to create practical applications that can simplify content generation. In this example, I entered a brief description of neural networks, and the model quickly provided a relevant title. 🔧 Built on Google Colab and deployed with ngrok. Always eager to learn, innovate, and apply technology in creative ways. Looking forward to exploring more possibilities with NLP! #NLP #MachineLearning #AI #TitleGenerator #NaturalLanguageProcessing #Innovation #Projects
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Just completed the DeepLearning.AI Natural Language Processing Specialization. While I appreciate the review of foundational knowledge gained from exploring historical approaches like BOW, HMMs and LSTMs, I would rather spend more time on the cutting-edge advancements in NLP, particularly delving deeper into the capabilities of Hugging Face Transformers. All those certifications are fun, but I always feel let down because they are either too much from scratch, not professionalizing enough, or not focused on the current state-of-the-art. What are your thoughts? #LLM #NLP #deeplearning
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"Excited to share that I've completed the NLP Foundations program! During this journey, I deepened my knowledge of Natural Language Processing, covering essential topics like text preprocessing, tokenization, sentiment analysis, named entity recognition, and more. I explored practical implementations, refined data extraction, and gained hands-on experience with cutting-edge tools in NLP. This program has strengthened my passion for AI, and I'm ready to leverage these skills to build smarter, more intuitive solutions. Thanks to iNeuron.ai Here's to continuous learning and the power of language! 🚀 #NLP #AI #DeepLearning #iNeuron #SkillBuilding"
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Last month, I submitted my undergraduate thesis book, where we researched on "Automated Literature Review Generation using NLP Techniques & Retrieval Augmented Generation utilizing LLM". Our main contributions were: 1. To develop a system to automatically generate the Literature Review segment of a research paper by using only the PDFs of the related papers as input. 2. Comparing results among various natural language processing approaches, such as: - Transformer: SimpleT5 model - Frequency-based approach: spaCy Library - Large Language Model: GPT-3.5-TURBO-0125 Watch the video for the conceptual tool demo. Currently, it is hosted locally with basic features. We plan to deploy the web tool in the future with additional customization options and model choices, such as Bert, Gemini, and LLaMA. I want to especially thank our supervisor, T Gopi Krishna Sir, for his guidance, and my thesis mates Mahdi Mohtasim and Shakil Mosharrof for their contributions. #NLP #AI #LLM
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A good list of Research Papers that you should read!
Natural Language Processing (NLP) is a critical subfield of AI that plays a crucial role in many areas. Reading research papers is essential to staying current and advancing in the field of NLP. Save this post for later, tag someone who might be studying NLP and let us know in the comments about your experience of reading research papers! 1. Universal Language Model Fine-tuning for Text Classification : https://lnkd.in/dywd43vB 2. Speech and Language Processing : https://lnkd.in/eDb94ve 3. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding : https://lnkd.in/gEiVBwJ 4. Efficient Estimation of Word Representations in Vector Space : https://lnkd.in/dXeEc8qH 5. Attention Is All You Need : https://lnkd.in/dcYWWd6 6. Sequence to Sequence Learning with Neural Networks : https://lnkd.in/dENiyMG4 7. Bag of Tricks for Efficient Text Classification : https://lnkd.in/bDWP2rh #NLPResearchPapers #NaturalLanguageProcessing #GENAI #DeepLearning
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Hello, I'm excited to share my latest Medium article: "Text Representation in NLP: Comparison of TF-IDF with Count Vectors, Step-by-Step Guide to Calculating the TF-IDF Formula (Original and Smoothed), and L2 Normalization". The article analyzes the differences between TF-IDF and Count Vectors and explains in detail how the TF-IDF formula is calculated in both variants. Additionally, it illuminates the role of L2 normalization for the stability and comparability of vectors. The article is available in German and English. #NLP #TFIDF #CountVectors #MachineLearning #MediumArticle
Text Representation in NLP: Comparing TF-IDF with Count Vectors and a Step-by-Step Guide to…
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🚀 New Blog Post Alert! 🚀 I'm thrilled to share my latest Medium article: "Transformers Beyond NLP: Applications in Reinforcement Learning and More". In this post, I explore how Transformers are breaking out of their NLP roots and making waves in areas like reinforcement learning, computer vision, and more. Discover how this versatile architecture is being adapted to solve problems across a wide range of fields! Join me in exploring the exciting possibilities of Transformers beyond natural language processing! 🌟 https://lnkd.in/dhrRwxVq #MachineLearning #DataScience #AI #Transformers #ReinforcementLearning #DeepLearning #Blogging #Medium #TechEducation #MLStudents #AIResearch #Innovation
Transformers Beyond NLP: Applications in Reinforcement Learning and More
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Recently, I've been exploring the fascinating capabilities of Large Language Models (LLMs) and their impact on natural language processing. As part of this learning journey, I developed a summarization tool called "smmrz-it" (Summarize-It) which uses LaMini-LM. While the tool itself isn't unique but it has served as a valuable exercise in understanding how LLMs process and has helped me grow interest into the field. If you're interested in seeing it in action or want to peek at the code, feel free to reach out to me. StreamLit Link : https://lnkd.in/dfFFuYES GitHub Repository : https://lnkd.in/dQUEjF6u #LLMs #AI #Summarization #NLP #Streamlit
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