
Python Machine Learning & Predictive Analytics
About this course
Data is the new oil, but without machine learning, it's just raw information. In today's tech-driven economy, the ability to build predictive models is one of the most lucrative and highly sought-after skills by employers across the globe. Whether you want to predict stock market trends, identify customer churn, or build image recognition tools, this course is your complete roadmap."Python Machine Learning & Predictive Analytics" is designed to take you from understanding basic data structures to deploying advanced artificial intelligence models.
We bypass the heavy, intimidating academic math and focus entirely on highly practical, applied programming.In this course, we start with the essentials of data preprocessing—teaching you how to clean, scale, and manipulate messy real-world datasets using Pandas and NumPy. From there, we dive into Supervised Learning, building powerful Regression and Classification models like Random Forests, Support Vector Machines, and Gradient Boosted Trees. You will learn exactly how to evaluate your models using professional metrics like ROC-AUC, Precision, and Recall.Finally, we transition into the cutting-edge world of Deep Learning.
You will learn how to build, train, and deploy complex Neural Networks using the industry-standard Keras and TensorFlow libraries. By the end of this course, you will have a robust portfolio of functioning predictive models to show prospective employers.Basic infoCourse locale: English (US) or your preferred localeCourse instructional level: All LevelsCourse category: DevelopmentCourse subcategory: Data ScienceWhat is primarily taught in your course? (Topic): Machine Learning
Skills you'll gain
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Course Information
Level: All Levels
Suitable for learners at this level
Duration: Self-paced
Total course content
Instructor: Udemy Instructor
Expert course creator
This course includes:
- 📹Video lectures
- 📄Downloadable resources
- 📱Mobile & desktop access
- 🎓Certificate of completion
- ♾️Lifetime access
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