In this two-hour video, you'll learn how to use advanced tools in Python for data analysis. Building on the basics of reading, querying, and interacting with data using pandas, we'll dive into machine learning with scikit-learn. This course covers techniques like linear regression, neural networks, and deep learning, focusing on predicting Y from X data. If you're looking to deepen your understanding of data analysis and machine learning in Python, this course is perfect for you!
Social Media Links:
instagram: [ Ссылка ]
Youtube: [ Ссылка ]
Discord: [ Ссылка ]
Support and Donations:
BuyMeACoffee: [ Ссылка ]
[ Ссылка ]
This video provides a comprehensive introduction to the principles behind neural networks, explaining how they learn and recognize patterns. The speaker uses a simple example of a four-pixel camera to illustrate how neural networks can be trained to recognize different types of images, such as solid, vertical, diagonal, or horizontal lines. The video covers key concepts, including input neurons, weighted connections, sigmoid functions, rectified linear units, and backpropagation. It also discusses how neural networks can be trained using error calculation and gradient descent. The speaker provides a clear and concise explanation of the underlying math and concepts, making it accessible to those new to the field of neural networks
Social Media Links:
instagram: [ Ссылка ]
Youtube: [ Ссылка ]
Discord: [ Ссылка ]
Support and Donations:
BuyMeACoffee: [ Ссылка ]
[ Ссылка ]
Additional Resources:
Fundamental Books for Machine Learning from Experts (Part 1): [ Ссылка ]
Advanced Books for Machine Learning from Experts(Part 2): [ Ссылка ]
Assessing Password Strength with Machine Learning in Python: [ Ссылка ]
Machine Learning with Python: Top Libraries and Their Examples: [ Ссылка ]
#python #dataanalysis #machinelearning #panda #scikitlearn #neuralnetworks #deeplearning #datascience #pythontutorial #machinelearning
