The Complete Linear and Logistic Regression Course in Python

Lasso and Ridge Regression, Elastic Net Regression, Linear Regression, Logistic Regression, pickle, tempfile.

Created by: Hoang Quy La
Electrical Engineer

What Will I Learn?

• Tensorflow
• Tensorboard
• pandas
• ReLU activation function.
• Seaborn
• Google Colab
• Import data from the UCI repository.
• scikit-learn
• Logistic Regression.
• Linear Regression.
• numpy
• pickle
• tempfile
• Lasso and Ridge Regression
• Elastic Net Regression
• Multiple and multivariate linear regression
• TensorFlow Keras API

Requirements

• Basic knowledge of Python is required.

Target audience

• Anyone interested in Machine Learning.
• Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
• Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
• Any students in college who want to start a career in Data Science
• Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.