I have completed DataCamp's Introduction to Deep Learning with Keras!
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Completed Introruction to Deep Learning with Keras Course by Datacamp
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Deep dive into deep learning with Keras.🤿
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I am thrilled to have earned my certificate in 'Introduction to Deep Learning with Keras'!
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Data Engineer | LLM | English B2 | Machine Learning | Microsoft Fabric | Python | PySpark | SQL | Power BI | Azure | Databricks | Data Factory | Synapse | Scikit Learn | DataStage | Airflow | Splunk
Introduction to Deep Learning with Keras
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Second year AI and Analytics Student in Singapore Polytechnic | Aspiring Data Analyst | Seeking an internship in the AI industry
Introduction to Deep Learning with Keras!
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Deeplearning.ai Mentor 👨🏫 | Data Scientist 🧠 | Statistician 📈 | Programmer 💻 | Medical Student 🩺 | Helping businesses in data-driven decisions
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Unity Game Developer | Flutter App Developer | Information Technology Undergraduate Student at Gadjah Mada University
I have finished "Introduction to Deep Learning with Keras" in DataCamp!
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A growth driven data analyst looking for challenging opportunities| Analyst | Business Analyst | Power BI | Tableau | Excel | R | Python | Data Enthusiast |Growth Hacker
Great insights, Nikita! Regularization techniques like L1 and L2 are crucial for improving model performance and preventing overfitting. Thanks for sharing these valuable resources and implementations in Keras . Early stopping is another fantastic method to ensure optimal training duration. Looking forward to more data-driven insights from you!
Distilling down Data for Actionable Takeaways | Data Scientist | Data Analyst | Product Analyst | Data Science and Analytics Writer | NSIT'22
Regularization Techniques in Deep Learning 👇 ➡️ (Don't Miss) Most Important Concept for all Data Enthusiasts 🛠️ Regularization technique used in deep learning to prevent overfitting by adding a penalty term to the loss function. 💻 Github Repository (⭐ this repo): 🔗 https://lnkd.in/gAjHJAsm 💡There are several types of regularization techniques for neural networks. We’ll discuss L1 and L2 regularization techniques and their Keras implementations here: 🔗 https://lnkd.in/gAjHJAsm In-case you have missed, here is the link to another popular technique called, Early stopping to handle overfitting in model: https://lnkd.in/g88m53h6, it is used to stop the model training at an appropriate time - before the model overfits, rather than addressing the issue of overfitting directly. 👈 However, regularization is a more robust technique that can be used to avoid overfitting. Whether you’re a beginner diving into deep learning or an expert, understanding the Basics of Regularization Techniques help you effectively apply it to real-world problems. 🏄♂️🐍 Happy learning! 🚀🌟 ——— 💬 Share your thoughts in comments; it will be valuable for me. ⬇️ 📍 Stay tuned with Nikita Prasad for more data-driven insights. 📈🔍 ——— #dataengineer #dailycoding #engineer #machinelearningengineer #machinelearning #statistics #stats #datainsights #datascience #neuralnetworks #datascientist #selfteaching #coding #softwareengineer #programming #analyticalnikita #dataanalystlearning #learntocode #programmingtips #programminglife #womeninstem #dataanalysis #dataengineering #dlmodels #deeplearning #researchassistant
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I have successfully completed the Introduction to Deep Learning with Pytorch course on DataCamp!! ✔
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Completed this awesome course on Deep Learning using PyTorch
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Fantastic work Ethan Chua! Use this accomplishment as a springboard to reach even greater heights in your coding career. Wishing you continued success and fulfillment! We are cheering you on along your journey!💪👩💻🌟