PCA using Python (scikit-learn, pandas) Codementor

#artificialintelligence

My last tutorial went over Logistic Regression using Python. One of the things learned was that you can speed up the fitting of a machine learning algorithm by changing the optimization algorithm. A more common way of speeding up a machine learning algorithm is by using Principal Component Analysis (PCA). If your learning algorithm is too slow because the input dimension is too high, then using PCA to speed it up can be a reasonable choice. This is probably the most common application of PCA. Another common application of PCA is for data visualization.


Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data: Ankur A. Patel: 9781492035640: Amazon.com: Books

#artificialintelligence

Most of the successful commercial applications to date--in areas such as computer vision, speech recognition, machine translation, and natural language processing--have involved supervised learning, taking advantage of labeled datasets. However, most of the world's data is unlabeled. In this book, we will cover the field of unsupervised learning (which is a branch of machine learning used to find hidden patterns) and learn the underlying structure in unlabeled data. According to many industry experts, such as Yann LeCun, the Director of AI Research at Facebook and a professor at NYU, unsupervised learning is the next frontier in AI and may hold the key to AGI. For this and many other reasons, unsupervised learning is one of the trendiest topics in AI today.


PCA using Python (scikit-learn) – Towards Data Science

@machinelearnbot

My last tutorial went over Logistic Regression using Python. One of the things learned was that you can speed up the fitting of a machine learning algorithm by changing the optimization algorithm. A more common way of speeding up a machine learning algorithm is by using Principal Component Analysis (PCA). If your learning algorithm is too slow because the input dimension is too high, then using PCA to speed it up can be a reasonable choice. This is probably the most common application of PCA.


Machine Learning With Python - Hierarchical Clustering Advantages & Disadvantages

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Enroll in the course for free at: https://bigdatauniversity.com/courses... Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning. This #MachineLearning with #Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!


Machine Learning With Python - Machine Learning vs Statistical Modeling

#artificialintelligence

Enroll in the course for free at: https://bigdatauniversity.com/courses... Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends. This free Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning. This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!