All the important and general machine learning algorithm implimentation
- Recomendation systeam:
Recomendation system has well known applications.I have used collaborative filtering learning algorithm and apply it to a dataset of movie ratings.
- Anomaly detection:
It is used to find some unusal activity.I have implemented an anomaly detection algorithm to detect anomalous behavior in server computers.
- Linear regression:
It is an important algorithm for prediction of continuous values based on data. I have implemented the algorithm with one varible for food truck profit and with multivariable for housing prices.
- Logistic regreesion:
It is classifiction algorithm where we plot a line and make distiction among classes.The problem I have choosen is if the student will get the admission in university or not.
- regularized logistic regression:
I have implemented regularized logistic regression to predict whether microchips from a fabrication plant passes quality assurance.(In folder of Logistic reg.)
- Muti-class classification:
I have used logistic regression , neural networks to recognize handwritten digits between 0 to 9.
- Neural Network:
This code contains the backpropogation step to train the neural network.
- Support Vector machine:
I have used SVM for spam classification of the mails.
- K-means:
K-means is one of the basic custring algorithm.I have used it for the image compression which is an interesting used case.
- PCA:
Priciple componet analysis is the dimensionality reduction algorithm and is very important for the removing unimportant data which is not going to affect the results by huge amount.