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🚀 Excited to announce our latest blog post on "Persian Homograph Disambiguation: Leveraging ParsBERT for Enhanced Sentence Understanding with a Novel Word Disambiguation Dataset". This study introduces a new dataset tailored for Persian homograph disambiguation and explores various embeddings' efficacy in downstream tasks. We also scrutinize the performance of lightweight machine learning and deep learning models, providing valuable insights and guidance for practitioners. This research empowers researchers and practitioners to effectively tackle homograph-related challenges. Read the full post here: https://bit.ly/45gh7E8.

It all started with N-BEATS in 2020, which was followed by NHITS in 2022. In 2023, PatchTST and TSMixer were proposed, and they still rank among the top forecasting models. More recently, discovered the iTransformer, which further pushed the performance of deep learning forecasting models. Now, we introduce the Series-cOre Fused Time Series forecaster or SOFTS.

💡 What can you expect at PyData NYC 2024? From deep learning algorithms to responsible AI moderation, our schedule is packed with insightful talks and tutorials. Whether you're a beginner or an experienced practitioner, there's something for everyone! See for yourself at PyData NYC 2024, Nov. 6-8 https://hubs.la/Q02VwY3Y0

🌟 Exciting News Alert! Discover the Power of K-Values in Shaping Decision Surfaces Across Eight Unique Datasets! 🌟 🔍 Embark on a Journey into the Fascinating Realm of Machine Learning: Unraveling the Mystery of Decision Surfaces! 🔍 📊 As part of my continuous exploration in machine learning, I've ventured into the realm of understanding how different K-values influence decision surfaces across eight diverse datasets: Udata, Concentriccir1, Concentriccir2, Linearsep, Outlier, Overlap, XOR, and Twospirals. 🔍 Deciphering Decision Surfaces: Decision surfaces stand at the core of machine learning, serving as the defining boundaries that separate various classes or categories within a dataset. Through visualizing these surfaces, we gain invaluable insights into how our classification models interpret and differentiate between individual data points. 🔢 The Significance of K-Values: The choice of K-value emerges as a pivotal hyperparameter in K-Nearest Neighbors (KNN) classification, dictating the number of nearest neighbors considered during prediction. Through meticulous experimentation and analysis, I've delved deep into the impact of varying K-values on decision surfaces, offering profound insights into model behavior and performance. 🔎 Insights Across Diverse Datasets: Across the spectrum of Udata, Concentriccir1, Concentriccir2, Linearsep, Outlier, Overlap, XOR, and Twospirals datasets, I've unearthed captivating variations in decision surfaces. Each dataset presents its unique set of challenges and characteristics, from subtle nuances to glaring distinctions, enriching our comprehension of machine learning algorithms' adaptability across diverse contexts. 📈 Unlocking New Frontiers: By unraveling the intricacies of decision surfaces and the influence of K-values, we empower ourselves to make informed decisions in model selection and optimization. These insights pave the way for heightened accuracy, resilience, and generalization capabilities across an extensive array of machine learning applications. Join me in this exhilarating journey of exploration and discovery at Innomatics Research Labs! https://lnkd.in/gTGxYv_7 #machinelearning #ai #datascience #innomaticsresearchlabs

🚀 Unlock the Future with Our Machine Learning & AI Radar Webinar Join us for an insightful session led by our CTO, Srikanth Victory. Discover the key objectives and overarching vision of the Machine Learning & AI Radar. This Radar is designed to help you evaluate the maturity of your data science, machine learning, and AI initiatives in today's fast-paced market. Ready to elevate your capabilities? Learn more here and reach out to us!

NeurIPS 2024 is just one week away! 🎉 Join us in Vancouver at Booth #103 as we connect with the brightest minds in AI and machine learning. ✅ Explore how Anaconda is powering innovation in data science and AI. ✅ Book a meeting with our experts to learn how we can support your next breakthrough. See you there! Book here 🔗 https://lnkd.in/giu86prk

Check out my blog at https://lnkd.in/gUnUWz7z You can expect to see some amazing posts on the future of AI, ML and Data Science.

💡 Exploring the hurdles in generative AI adoption! Ilia Badeev, Data Science Lead from Trevolution Group shares insights with PYMNTS about the challenges and risks involved. Dive into the details: https://lnkd.in/gV_hsvhC

💡 Exploring the hurdles in generative AI adoption! Ilia Badeev, Data Science Lead from Trevolution Group shares insights with PYMNTS about the challenges and risks involved. Dive into the details: https://lnkd.in/gV_hsvhC

We know ... a session on Deep Learning might sound intimidating, but don't worry! During this upcoming webinar, Intissar EL AHMER will show us the foundations and applications of Deep Learning from a critical and analytical perspective. ➡ No coding needed ➡ No technical background needed You just need your laptop (or preferred device) and your enthusiasm to continue this AI Expedition. Tag a friend or colleague who can benefit from this session and make sure you have already registered. Link: https://lnkd.in/gEQt8MxC