The Complete Machine Learning Course with Python
Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!
4.50 (7669 reviews)

43 374
students
17.5 hours
content
Apr 2025
last update
$99.99
regular price
What you will learn
Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course!
Solve any problem in your business, job or personal life with powerful Machine Learning models
Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells & more
Go from zero to hero in Python, Seaborn, Matplotlib, Scikit-Learn, SVM, unsupervised Machine Learning etc
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Our Verdict
This course offers valuable insights for those who already possess foundational understanding in machine learning concepts. However, a beginner-friendly approach isn't present; prior knowledge is assumed, which could alienate some learners. The lack of practice exercises leaves learners without hands-on experience to apply the techniques discussed throughout the course. Ultimately, this comprehensive overview might suit advanced students or those already familiar with core concepts who seek exposure to a wide array of machine learning and deep learning topics. Keep in mind that this isn't an ideal starting point for newcomers; optimum value is derived from existing contextual knowledge.
What We Liked
- Covers a lot of valuable information and techniques related to machine learning and deep learning
- Includes updated codes that work with Python 3.6, 3.7, and Google Colab
- Provides examples of real-world applications, such as computer vision using Convolutional Neural Networks
- Explains foundational concepts in a comprehensive manner
Potential Drawbacks
- Lacks practice exercises, making it hard for learners to apply their knowledge
- Jumps around between topics and lacks clarity, potentially causing confusion
- Assumes prior knowledge of statistics, coding, and specific libraries
- Some learners might find the course too long and demanding with little practical guidance
Related Topics
1382702
udemy ID
06/10/2017
course created date
31/07/2019
course indexed date
561nano
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