פיתוח של רשתות נוירונים בפייתון בעזרת machine learning

Unlock the power of neural networks with this comprehensive course! We'll cover both the mathematical foundations and the practical application of neural networks, equipping you with the skills to build and deploy intelligent systems.

You'll dive into real-world examples, including:

• Image recognition: Learn to build models that identify objects in images.
• Audio file recognition: Develop systems to classify and understand audio.
• Property valuation: Explore how neural networks can be used to estimate home values.
• And much more!

This course explores key techniques like:

• Convolutional Neural Networks (CNNs): Master CNN architectures, including Conv2D, pooling, strides, and padding, for powerful image processing.
• Regression: Understand and apply regression techniques for predicting continuous values.
• Optimization methods: Explore various optimization strategies to improve model performance, including SGD (Stochastic Gradient Descent) and Backpropagation.
• Regularization: Prevent overfitting with techniques like L1 & L2 Regularization and Dropout.
• Loss functions & Activation functions: Gain a deep understanding of Cross Entropy Loss Function and Softmax Activation Function.
• Data Augmentation: Improve model robustness through data augmentation techniques.
• Batch Normalization: Learn to stabilize and accelerate training.
• Transfer Learning: Leverage pre-trained models for faster and more effective development.
• Feature Extraction: Extract meaningful features from data for improved model accuracy.

You'll also gain hands-on experience with practical aspects like:

• Saving and loading models: Implement checkpoints and callbacks for efficient model management.
• Using existing models for prediction: Deploy trained models for real-time predictions.
• Building custom layers: Learn various methods for constructing sophisticated neural network architectures.
• Functional API: Utilize the flexible Functional API for building complex models.

Prerequisite: Basic programming knowledge in Python.

This course is perfect for anyone looking to learn about deep learning, machine learning, and artificial intelligence. Develop valuable skills in neural network development and unlock exciting career opportunities!