http://archive.is/wip/V6q44 Classification-Based Machine Learning is Archive: for FinanceHands on guide on using classification based Machine Learning techniques with application in finance and investmentFinally, a comprehensive hands-on machine learning course with specific focus on classification based models for the investment community and passionate investors.In the past few years, there has been a massive adoption and growth in the use of data science, artificial intelligence and machine learning to find alpha..
Archive: http://archive.is/wip/V6q44 Classification-Based Machine Learning for FinanceHands on guide on using classification based Machine Learning techniques with application in finance and investmentFinally, a comprehensive hands-on machine learning course with specific focus on classification based models for the investment community and passionate investors.In the past few years, there has been a massive adoption and growth in the use of data science, artificial intelligence and machine learning to find alpha.
information is However, on and application of machine learning to investment are scarce..
However, information on and application of machine learning to investment are scarce.
This course is has been designed to address that..
This course has been designed to address that.
It is is meant to spark your creative juices and get you started in this space.In this course, we are first going to provide some background information to machine learning..
It is meant to spark your creative juices and get you started in this space.In this course, we are first going to provide some background information to machine learning.
ease is To you into the machine learning lingo, we start will something that most people are familiar with – Logistic Regression..
To ease you into the machine learning lingo, we start will something that most people are familiar with – Logistic Regression.
The assumptions is of financial time series as well as the stylized facts are introduced and explained at length due to its importance..
The assumptions of financial time series as well as the stylized facts are introduced and explained at length due to its importance.
The assumptions of linear regression is are also highlighted to demonstrate the challenges and danger of blindly applying machine learning to investment without proper care and considerations to the nuances of financial time series.After covering the basics of classification based machine learning using logistic regression, we then move on to more advanced topics covering other classification machine learning algorithms such as Linear Discriminant Analysis, Quadratic Discriminant Analysis, Stochastic Gradient Descent classifier, Nearest Neighbors, Gaussian Naive Bayes and many more..
The assumptions of linear regression are also highlighted to demonstrate the challenges and danger of blindly applying machine learning to investment without proper care and considerations to the nuances of financial time series.After covering the basics of classification based machine learning using logistic regression, we then move on to more advanced topics covering other classification machine learning algorithms such as Linear Discriminant Analysis, Quadratic Discriminant Analysis, Stochastic Gradient Descent classifier, Nearest Neighbors, Gaussian Naive Bayes and many more.
We is follow the foundations that we started in the first regression based machine learning course covering cross-validation, model validation, back test, professional Quant work flow, and much more.This course not only covers machine learning techniques, it also covers in depth the rationale of investing strategy development.This course is the second of the Machine Learning for Finance and Algorithmic Trading & Investing Series..
We follow the foundations that we started in the first regression based machine learning course covering cross-validation, model validation, back test, professional Quant work flow, and much more.This course not only covers machine learning techniques, it also covers in depth the rationale of investing strategy development.This course is the second of the Machine Learning for Finance and Algorithmic Trading & Investing Series.
The courses is in the series includes:Regression-Based Machine Learning for Algorithmic TradingClassification-Based Machine Learning for Algorithmic TradingEnsemble Machine Learning for Algorithmic TradingUnsupervised Machine Learning: Hidden Markov for Algorithmic TradingClustering and PCA for InvestingIf you are looking for a course on applying machine learning to investing, the Machine Learning for Finance and Algorithmic Trading & Investing Series is for you..
The courses in the series includes:Regression-Based Machine Learning for Algorithmic TradingClassification-Based Machine Learning for Algorithmic TradingEnsemble Machine Learning for Algorithmic TradingUnsupervised Machine Learning: Hidden Markov for Algorithmic TradingClustering and PCA for InvestingIf you are looking for a course on applying machine learning to investing, the Machine Learning for Finance and Algorithmic Trading & Investing Series is for you.
over 30 machine learning techniques is With test cases, which included popular techniques such as Lasso regression, Ridge regression, SVM, XGBoost, random forest, Hidden Markov Model, common clustering techniques and many more, to get you started with applying Machine Learning to investing quickly.Course CurriculumIntroductionIntroduction (3:07)Feedback (4:26)Obtaining the Course Resources (3:28)How to Succeed In This Course (6:03)Introduction To Machine Learning For Algorithmic TradingBrief Introduction to Machine Learning (5:38)Machine Learning Project Check List Part 1 (12:43)Machine Learning Project Check List Part 2 (10:00)Model Selection and Quant Workflow (8:24)Financial Time Series Characteristics (5:58)Logistic RegressionUnderstanding Logistic Regression (11:16)Logistic Regression and Scikit Learn (13:55)Classification - A Walk Through TutorialUnderstanding Classification ML and Data Exploration (9:12)Building a Simple Classifier and Performing Cross Validation (15:23)Confusion Matrix (15:51)Precision/Recall Tradeoff (14:25)The Receiver Operating Characteristics (ROC) Curve (8:49)Default PredictionTemplate (10:27)Default prediction with LDA, KNN and Random Forest (12:10)Predicting Next Day's ReturnsBackground to Returns Prediction (9:14)Predicting Next Day's Returns Using Logistic Regression (10:01)Predicting Next Day's Returns Using LDA and QDA (7:33)Price Prediction Using Real Market Data from Quantopian (7:10)Back Test and Tear Sheet (16:03)IdeasIdeas (18:29)Global Stock Selection StrategyIntroduction to Alpha Factors (8:32)Global Stock Selection Strategy (7:13)Bonus SectionBonus Lecture (1:46).
With over 30 machine learning techniques test cases, which included popular techniques such as Lasso regression, Ridge regression, SVM, XGBoost, random forest, Hidden Markov Model, common clustering techniques and many more, to get you started with applying Machine Learning to investing quickly.Course CurriculumIntroductionIntroduction (3:07)Feedback (4:26)Obtaining the Course Resources (3:28)How to Succeed In This Course (6:03)Introduction To Machine Learning For Algorithmic TradingBrief Introduction to Machine Learning (5:38)Machine Learning Project Check List Part 1 (12:43)Machine Learning Project Check List Part 2 (10:00)Model Selection and Quant Workflow (8:24)Financial Time Series Characteristics (5:58)Logistic RegressionUnderstanding Logistic Regression (11:16)Logistic Regression and Scikit Learn (13:55)Classification - A Walk Through TutorialUnderstanding Classification ML and Data Exploration (9:12)Building a Simple Classifier and Performing Cross Validation (15:23)Confusion Matrix (15:51)Precision/Recall Tradeoff (14:25)The Receiver Operating Characteristics (ROC) Curve (8:49)Default PredictionTemplate (10:27)Default prediction with LDA, KNN and Random Forest (12:10)Predicting Next Day's ReturnsBackground to Returns Prediction (9:14)Predicting Next Day's Returns Using Logistic Regression (10:01)Predicting Next Day's Returns Using LDA and QDA (7:33)Price Prediction Using Real Market Data from Quantopian (7:10)Back Test and Tear Sheet (16:03)IdeasIdeas (18:29)Global Stock Selection StrategyIntroduction to Alpha Factors (8:32)Global Stock Selection Strategy (7:13)Bonus SectionBonus Lecture (1:46)