Deep Learning: Convolutional Neural Networks in Python

Use CNNs for Image Recognition, Natural Language Processing (NLP) +More! For Data Science, Machine Learning, and AI

Created by Lazy Programmers inc. | 13.5 hours on-demand video course

*** NOW IN TENSORFLOW 2 and PYTHON 3 ***

Learn about one of the most powerful Deep Learning architectures yet! The Convolutional Neural Network (CNN) has been used to obtain state-of-the-art results in computer vision tasks such as object detection, image segmentation, and generating photo-realistic images of people and things that don’t exist in the real world! This course will teach you the fundamentals of convolution and why it’s useful for deep learning and even NLP (natural language processing). You will learn about modern techniques such as data augmentation and batch normalization, and build modern architectures such as VGG yourself.

What you’ll learn

• Understand convolution and why it’s useful for Deep Learning
• Understand and explain the architecture of a convolutional neural network (CNN)
  Implement a CNN in TensorFlow 2
• Apply CNNs to challenging Image Recognition tasks
• Apply CNNs to Natural Language Processing (NLP) for Text Classification (e.g. Spam Detection, Sentiment Analysis)

Recommended Course by Lazy Programmers

Financial Analysis: Build a ChatGPT Pairs Trading Bot [NEW COURSES]

Math 0-1: Calculus for Data Science & Machine Learning [NEW COURSES]

Deep Learning Prerequisites: The Numpy Stack in Python (V2+)

Time Series Analysis, Forecasting, and Machine Learning in Python

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Machine Learning: Natural Language Processing in Python (V2)

Artificial Intelligence: Reinforcement Learning in Python

Deep Learning Prerequisites: Logistic Regression in Python

Bayesian Machine Learning in Python: A/B Testing

PyTorch: Deep Learning and Artificial Intelligence

Redeem Offer

Click to open site

Udemy

success 100%