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## Introduction to Trading, Machine Learning and GCP

13 个视频 （总计 57 分钟）, 1 个阅读材料, 3 个测验
13 个视频
The Quant Universe2分钟
Quant Strategies7分钟
Exchange and Statistical Arbitrage8分钟
Index Arbitrage2分钟
Statistical Arbitrage Opportunities and Challenges5分钟
Introduction to Backtesting5分钟
Backtesting Design6分钟
What is AI and ML ? What is the difference between AI and ML?58
Applications of ML in the Real World1分钟
What is ML?3分钟
1 个阅读材料
Welcome to Introduction to Trading, Machine Learning and GCP10分钟
3 个练习
Python Skills Assessment Quiz
Intro to AI and ML5分钟
2

## Supervised Learning and Forecasting

13 个视频 （总计 72 分钟）
13 个视频
Regression and classification11分钟
Short history of ML: Linear Regression7分钟
Short history of ML: Perceptron5分钟
Lab Intro: Building a Regression Model37
Introduction to Qwiklabs3分钟
Lab Walkthrough: Building a Regression Model9分钟
What is forecasting? - part 15分钟
What is forecasting? - part 24分钟
Choosing the right model and BQML - part 13分钟
Choosing the right model and BQML - part 22分钟
Lab Intro: Forecasting Stock Prices using Regression in BQML36
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12分钟
1 个练习
Forecasting
3

## Time Series and ARIMA Modeling

11 个视频 （总计 52 分钟）
11 个视频
AR - Auto Regressive7分钟
MA - Moving Average2分钟
The Complete ARIMA Model4分钟
ARIMA compared to linear regression7分钟
How can you get a variety of models from just a single series?1分钟
How to choose ARIMA parameters for your trading model4分钟
Time Series Terminology: Auto Correlation4分钟
Sensitivity of Trading Strategy4分钟
Lab Intro: Forecasting Stock Prices Using ARIMA32
Lab Walkthrough: Forecasting Stock Prices using ARIMA7分钟
1 个练习
Time Series
4

## Introduction to Neural Networks and Deep Learning

9 个视频 （总计 36 分钟）
9 个视频
Short history of ML: Modern Neural Networks8分钟
Overfitting and Underfitting6分钟
Validation and Training Data Splits4分钟
Why Google Cloud Platform?2分钟
What are AI Platform Notebooks1分钟
Using Notebooks1分钟
Benefits of AI Platform Notebooks2分钟
3 个练习
Model generalization
Module Quiz8分钟
3.8
71 条评论

### 来自Introduction to Trading, Machine Learning & GCP的热门评论

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

Good course that gives a lot of breadth as an introduction to machine learning in finance. Well put together

### Jack Farmer

Curriculum Director
New York Institute of Finance

Machine Learning Consultant

### 关于 Google 云端平台

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

### 关于 纽约金融学院

The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks....

## 关于 Machine Learning for Trading 专项课程

This Specialization is for finance professionals, including but not limited to: hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies. The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create long-term trading strategies, short-term trading strategies, and hedging strategies. To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....

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