In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks.
Introduction to Trading, Machine Learning & GCP
Ce cours fait partie de Spécialisation Machine Learning for Trading
Instructeur : Jack Farmer
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Ce que vous apprendrez
Understand the fundamentals of trading, including the concepts of trend, returns, stop-loss, and volatility.
Define quantitative trading and the main types of quantitative trading strategies.
Understand the basic steps in exchange arbitrage, statistical arbitrage, and index arbitrage.
Understand the application of machine learning to financial use cases.
Compétences que vous acquerrez
- Catégorie : Machine Learning applied to Finance
- Catégorie : Finance
- Catégorie : Trading
- Catégorie : Investment
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Il y a 4 modules dans ce cours
In this module you will be introduced to the fundamentals of trading. You will also be introduced to machine learning. Machine Learning is both an art that involves knowledge of the right mix of parameters that yields accurate, generalized models and a science that involves knowledge of the theory to solve specific types of problems.
Inclus
26 vidéos3 lectures4 devoirs1 élément d'application
In this module you will be introduced to supervised machine learning and some relevant algorithms commonly applied to trading problems. You will get some hands-on experience building a regression model using BigQuery Machine Learning
Inclus
6 vidéos1 lecture1 devoir2 éléments d'application
In this module you will learn about ARIMA modeling and how it is applied to time series data. You will get hands-on experience building an ARIMA model for a financial dataset.
Inclus
11 vidéos1 devoir1 élément d'application
In this module you'll learn about neural networks and how they relate to deep learning. You'll also learn how to gauge model generalization using regularization, and cross-validation. Also, you'll be introduced to Google Cloud Platform (GCP). Specifically, you'll be shown how to leverage GCP for implementing trading techniques.
Inclus
5 vidéos1 lecture2 devoirs1 sujet de discussion
Instructeur
Recommandé si vous êtes intéressé(e) par Machine Learning
New York Institute of Finance
Google Cloud
New York Institute of Finance
New York University
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