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Deep Learning Crash Course Part-2 | Master Neural Networks & AI Fundamentals

Codanics 3,003 3 months ago
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You can book One to one consultancy session with me on Mentoga: https://mentoga.com/muhammadaammartufail #codanics #dataanalytics #pythonkachilla #pkc24 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Python ka chilla 2024 You can now register for Python ka chilla 2024 This is a paid course which you can register and find more information at the following link: https://forms.gle/kUU3eZJsFRb7Cn6r8 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Here you can access all the codes and datasets from Python ka chilla 2024: https://github.com/AammarTufail/python-ka-chilla-2024 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ --------------------------------------------------------------------------------------------------------------------------------------- Welcome to Part-2 of our Deep Learning Crash Course! In this advanced installment, we dive into cutting-edge topics and real-world applications that build on the fundamentals introduced in Part-1. Whether you’re looking to advance your AI projects or deepen your understanding of complex neural network architectures, this video is designed for you. What You'll Learn in This Video: Recurrent Neural Networks (RNNs): Explore the architecture behind RNNs and understand how they are used for sequential data. LSTM & GRU: Learn how Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) overcome common challenges in RNNs, such as vanishing gradients. Time Series Analysis: Discover how to apply deep learning models to time series data for forecasting and trend analysis. Transfer Learning: Understand the concept of transfer learning, its benefits, and how to implement pre-trained models for your projects. Generative AI & GANs: Dive into the world of generative models, including Generative Adversarial Networks (GANs), and see how they can create realistic data and images. Complete Study Projects: Get hands-on insights through complete study projects that illustrate the practical applications of these advanced techniques. Why Watch This Video? Advanced Insights: Perfect for those who have grasped the basics and are ready to explore more sophisticated topics. Practical Applications: See live demos and projects that put theory into practice. Expert Guidance: Learn from detailed explanations, expert tips, and step-by-step walkthroughs to master advanced neural network concepts. Who Is This For? AI Enthusiasts & Practitioners Data Scientists & Machine Learning Engineers Developers Interested in Advanced Neural Networks Students & Researchers in AI Don’t Forget to: 👍 Like this video if you find it helpful 🔔 Subscribe for more in-depth tutorials and advanced deep learning content 💬 Comment below with any questions or topics you’d like us to cover in future videos --------------------------------------------------------------------------------------------------------------------------------------- ✅Our Free Books: https://codanics.com/books/abc-of-statistics-for-data-science/ ✅Our website: https://www.codanics.com ✅Our Courses: https://www.codanics.com/courses ✅Our YouTube Channel: www.youtube.com/@Codanics ✅ Our whatsapp channel: https://whatsapp.com/channel/0029Va7nRDq3QxRzGqaQvS3r ✅Our Facebook Group: https://www.facebook.com/groups/codanics ✅Our Discord group for community Discussion: https://discord.gg/QpvUKEtUJD ✉️For more Details contact us at [email protected] Timestamps: 00:00:00 Deep Learning Part-2 00:00:05 Deep Learning Part-1 is here 00:00:08 Recurrent Neural Network (RNN) 00:11:08 Deep Insights to RNN 01:09:31 RNN in Python with TensorFlow 01:24:01 Key Term in NLP 02:25:47 Sentiment Analysis in Python 03:12:16 LSTM in TensorFlow with Python 03:38:32 History of ANN, CNN, RNN, LSTM, GRU 04:28:45 LSTM vs GRU 04:53:24 Underfitting of a DL Model 05:01:13 Overfitting of a DL Model 05:07:51 Good Fit or Robust Model 05:12:27 How to Improve a Model fitness? 05:21:05 Reducing Overfitting of a DL Model 05:44:44 Transfer Learning 06:04:38 Transfer Learning in Python using TensorFlow 06:21:43 Generative AI 06:34:50 Key Terms in Generative AI 07:07:54 GenAI working in Python 07:15:07 GenAI is Now 07:30:08 AI meri job kha gaye 07:35:51 Transfer Learning for Image Classification 08:20:28 Python for Transfer Learning (A Case Study) 08:50:54 Progressive Growing GANs in python 09:41:58 TensorBoard for Hyperparameter Tuning 10:20:44 Diffusion Models 10:37:58 Stable Diffusion Model in Python 10:59:36 Transformers from Huggingface 11:32:38 Extro 11:33:12 Deep Learning Crash Course Part-1

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