/ML_Lab

"For Educational Purposes Only!"

Primary LanguageJupyter Notebook

ML_Lab

EXP 1 : Compute the distance travelled by the robot from current position after a sequence of movement and original point

EXP 2 : Creation of scatter plot using sepal length and petal width to separate the Species classes

EXP 3 : Calculate the Five Number Summary(Quartiles, IQR) for the attribute(age) of each employee at a Tea Factory

EXP 4 : Analyze the complexity of Heap sort, applied over different sized random lists

EXP 5 : Preprocess the given data to build good training sets (80%) and test sets (20%) by removing the missing values and imputing them with the mean value

EXP 6 : Examine the interrelations among the set of variables using Principal Component Analysis, display the PCA Components and generate Heatmap

EXP 7 : Manipulate the Twitter Data Set by removing the Punctuation, Numbers, Special Characters and word length

EXP 8 : Generate a word cloud for the Twitter dataset and retrieve the top 15 positive and negative tags

EXP 9 : Find core samples of high density and expand clusters from them using DBSCAN Clustering

EXP 10 : Split the iris dataset into train and test data (80%-20%) and train or fit the data into the model using K Nearest Neighbor Algorithm

EXP 11 : Evaluate the performance of Machine Learning algorithms using Confusion Matrix, Accuracy, Sensitivity, Specificity, Precision and Recall

EXP 12 : Emply linear regression to check the linearity between the

12(a) : Stock Price and interest rate
12(b) : Stock Price and unemployement rate