theKemmie/70-days-of-Machine-Learning

70 Days Pre-Bootcamp Online Class with Data Science Nigeria; Machine Learning Stream #DSN70daysofML # 70 days of Machine Learning _This repository was made to keep track of my progress during Data Science Nigeria's 70 days of Machine Learning_ * Day 1 - Introduction to Machine Learning * Day 7 - How Linear Regression works * Day 10 - R-Squared theory; Another name for R-squared error is Coefficient of Determination. Error is the distance between a point and a line of best fit. The error is squared to get a positive value of our error. * Day 13 - Introduction to K Nearest Neighbors algorithm; 'K' in the "K Nearest Neighbors" algorithm is a parameter that refers to the number of nearest neighbors to consider during voting process. K Nearest Neighbors algorithm is classified as supervised learning. Clustering is the process of dividing data points into a number of similar groups. * Day 21 - Understanding Vectors; The magnitude of a vector is denoted with Bars. Learnt how to calculate the magnitude of the vector. * Day 22 - Support Vector Assertion; Dot product is the relationship between the input and weight. If vector "u", dotted with vector "w + b" equals zero, it means that Vector u is on the decision boundary. If vector "u", dotted with vector "w + b" is greater or equal to zero, it means that the sample is of a class above the hyperplane. * Day 23 - Support Vector Machine Fundamentals; A support vector is a feature set that if moved, affects the position of the best separating hyperplane. * Day 24 - Support Vector Machine Optimization; Equation for hyperplane is X.W + b Support Vector Machines are less effective when the data is noisy and contains overlapping points. * Day 29 & 30 - Introduction to Kernels; Kernels are done using inner product. Kernels take two inputs and outputs the similarities. Inner Product is a projection of x1 onto x2. Kernel is represented using the greek letter "phi". Transformation of the old and creation of new hyperplane helps SVM to perform better on non-linearly separable data. The default kernel for SVM using sckit- …