Description
Machine Learning as a Course: AI Python and MLOps. Are you interested in machine learning? Then this course is right for you! This course is designed by a data scientist and a machine learning expert so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way. More than 900,000 students worldwide rely on this course. We will take you step by step into the world of machine learning. With each tutorial, you will develop new skills and improve your understanding of this challenging but rewarding subfield of data science. This course can be completed by doing Python tutorials, or R tutorials, or both – Python and R. Choose the programming language you need for your career. This course is fun and exciting while we dive deep into machine learning. It is structured as follows:
- Part 1 — Data Preprocessing
- Part 2 — Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
- Part 3 — Classification: Logistic Regression, k-NN, SVM, Kernel SVM, Simple Bayes, Decision Tree Classification, Random Forest Classification
- Part 4 – Clustering: K-Means, Hierarchical Clustering
- Part 5 – Teaching the rules of society: apriori, éclat
- Section 6 – Reinforcement Learning: Upper Confidence Limits, Thompson Sampling
- Part 7 — Natural Language Processing: Word Set Models and Algorithms for NLP
- Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
- Part 9 – Dimensionality Reduction: PCA, LDA, PCA Kernel
- Part 10 — Model Selection and Boosting: K-Fold Cross-Validation, Parameter Tuning, Network Search, XGBoost
Each section within each course is independent. So you can take the entire course from start to finish, or you can jump straight to a specific section and learn what you need for your career right now. Plus, the course is packed with practical exercises that are based on real case studies. So you will not only learn the theory, but you will also have plenty of practical exercises to build your own models. This course includes both Python and R code templates that you can download and use in your project.
What you will learn in the Machine Learning Edge: AI Python and MLOps course
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Learn which machine learning model to choose for each type of problem
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Get great intuition from multiple machine learning models
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Professor of Machine Learning in Python and R
This course is suitable for those who
- Anyone interested in machine learning.
- Anyone who is not comfortable with coding but is interested in machine learning and wants to easily apply it to datasets.
- Intermediate people who know the basics of machine learning, including classic algorithms like linear regression or logistic regression, but want to learn more and explore all the different areas of machine learning.
- All those people who are not satisfied with their job and want to become scientists.
- Students who have at least a high school background in mathematics and want to start learning machine learning.
- Anyone who is not comfortable with coding but is interested in machine learning and wants to easily apply it to datasets.
Machine Learning AZ Course Specifications: AI Python and MLOps
- Publisher: Udemy
- coach: Akhil Vidyula
- Training level: Beginner to advanced
- Training duration: 7 hours and 44 minutes
- Number of courses: 17
Machine Learning A-Z Course Topics: AI Python and MLOps
Machine Learning AZ Course Requirements: AI Python and MLOps
- Just some high school math level.
Machine Learning Edge Course Images: AI Python and MLOps
Sample video of the course
installation Guide
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download link
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