Applying Machine learning Algorithms on various data sets.
There are several projects on Machine Learning which are uploaded here for practice and references. You can learn end to end model building in Machine Learning with these starter projects. Various NLTK, Deep Learning projects are also uploaded for practice.
Iris dataset one of the most basic dataset to learn and understand supervised machine learning alogothims and how do they work. I have done the data exploration , data visulaization of the IRIS data set Gone further in training the model by various Machine learning algorithms like Regression algorithm (Linear Regression), another is Instance based learning algorithm like K-NN which does not create model. Iris data is also tested upon the Decision Tree algorithm. We notice that Decision Tree Classifier gives te maximum accuracy when compared with the other two. We move on further and check six various algorthims. SVM give 93% accuracy.
Boston Data is a house pricing data and I have applied Linear Regression to train the model. The score is not great means that model might not perform well when given data to predict prices.
Other projects include Wine Dataset, Adult UCI Income Dataset, Amazon Forrd review, content based Movie Recommender system and others.
You can additional help from my YouTube Channel: https://www.youtube.com/c/PriyankaSharmastudyclub