More ML terminology

Author: usrbinomarbash

Machine Learning/README.md

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+## Terminology and Techniques
+
+
+- Clustering: Putting data together which have similar characteristics into dense cluster in an unsupervised way
+
+### Types of Algo in Clustering:
+- K Means Clustering
+- Hierarchial Clustering
+- DBSCAN Clustering
+- Expectation Maximization Clustering
+
+### Optimization in ML
+
+- Find the ideal model weights which reduces the loss between predicted and actual value
+- whilst remembering to obtain the best fit of a certain dataset to the model  
+
+
+### Cross-Validation:
+- Gives you the performance of your ML model depending on the new unseen data
+
+### Functions You Must Know in Each Category of ML
+
+#### Classification
+
+1. Log
+2. Hinge
+3. Exponential
+4. Cross Entropy
+5. Kullback Leibler Divergence
+
+#### Regression
+
+1. Huber, , , , Mean Squared Error/ L2, Mean Squared Logarithm Error/ L2,
+2. Quantile
+3. Log Cosh
+4. Mean Absolute Error/ L1
+5. Mean Squared Error/ L2
+6. Mean Squared Logarithm Error/ L2