What you’ll learn
- Applications of Machine Learning to various data, Unsupervised Learning, Supervised Learning
The course contents are given below:
- Introduction to Machine Learning
- Introductions to Deep Learning
- Installations
- Unsupervised Learning
- Clustering, Association
- Agglomerative, Hands-on
- DBSCAN, Hands-on
- Mean Shift, Hands-on
- K Means, Hands-on
- Association Rules, Hands-on
- (PCA: Principal Component Analysis)
- Supervised Learning
- Regression, Classification
- Train Test Split, Hands-on
- k Nearest Neighbors, Hands-on
- kNN Algo Implementation
- Support Vector Machine (SVM), Hands-on
- Support Vector Regression (SVR), Hands-on
- SVM (non linear svm params), Hands-on
- SVM kernel trick, Hands-on
- SVM mathematics
- Linear Regression, Hands-on
- Gradient Descent overview
- One Hot Encoding (Dummy vars)
- One Hot Encoding with Linear Regr, Hands-on
- Info about Datasets
How to Enroll Machine Learning with Python: SVM,Kmeans,KNN,LinReg,PCA,DBS course?
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