Machine Learning and Deep Learning Bootcamp in Python

Interested in Machine Learning and Deep Learning . Then this course is for you. This course is about the fundamental concepts of machine learning, deep learning, reinforcement learning and machine learning.

These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. We will use Python with SkLearn, Keras and TensorFlow.

### MACHINE LEARNING ###Linear Regressionunderstanding linear regression modelcorrelation and covariance matrixlinear relationships between random variablesgradient descent and design matrix approachesLogistic Regressionunderstanding logistic regressionclassification algorithms basicsmaximum likelihood function and estimationK-Nearest Neighbors Classifierwhat is k-nearest neighbour classifier. non-parametric machine learning algorithmsNaive Bayes Algorithmwhat is the naive Bayes algorithm. classification based on probabilitycross-validation overfitting and underfittingSupport Vector Machines (SVMs)support vector machines (SVMs) and support vector classifiers (SVCs)maximum margin classifierkernel trickDecision Trees and Random Forestsdecision tree classifierrandom forest classifiercombining weak learnersBagging and Boostingwhat is bagging and boosting.

AdaBoost algorithmcombining weak learners (wisdom of crowds)Clustering Algorithmswhat are clustering algorithms. k-means clustering and the elbow methodDBSCAN algorithmhierarchical clusteringmarket segmentation analysis### NEURAL NETWORKS AND DEEP LEARNING ###Feed-Forward Neural Networks single layer perceptron modelfeed. forward neural networksactivation functionsbackpropagation algorithmDeep Neural Networkswhat are deep neural networks.