A guide to learn Machine Learning and Deep Learning
Firstly, start with learning statistics including mean, standard deviation, variance and other terms.
After this start with learning the following topics,
- Linear Regression (Learn about p-value, t-statistics, ANOVA)
- Logistic Regression
- Support Vector Machine (Kernel)
- Principal Component Analysis (PCA)
- Neural Networks (Backpropogation)
- Convolutional Neural Network
- K-Nearest Neighbor
- K-Means Clustering
- Agglomerative Clustering
These are the topics that are important to gain knowledge in Machine Learning.
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