You can book One to one consultancy session with me on Mentoga: https://mentoga.com/muhammadaammartufail
#codanics #dataanalytics #pythonkachilla #pkc24
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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
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Here you can access all the codes and datasets from Python ka chilla 2024: https://github.com/AammarTufail/python-ka-chilla-2024
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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
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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