We can't find the internet
Attempting to reconnect
Something went wrong
Hang in there while we get back on track
£51.99
This is the most expensive it has ever been. Walk away.
£52 today · previous high £52 · all-time low £18
Packt Publishing Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python
Price data last checked 45 day(s) ago - refreshing...
We'll watch every seller, every day. One email when your price arrives.
Price History & Forecast
Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.
Last 46 days · 46 data points (no recent data)
Historical
Generating forecast…
Price data last checked 45 day(s) ago - refreshing...
NEW HERE?
Amazon shows you one price. We show you all of them.
Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.
WHAT'S ON THIS PAGE
↑ Price chart
when this has been cheap or pricey
when this has been cheap or pricey
↑ Forecast
where the price is heading next
where the price is heading next
↓ Statistics
all-time high & low, recent range
all-time high & low, recent range
↑ Price alert
name your number, we'll email you
name your number, we'll email you
Price Distribution
Price distribution over 46 days • 2 price levels
Current Price
Price Analysis
Most common price: £52 (32 days, 69.6%)
Price range: £18 - £52
Price levels: 2 different prices over 46 days
Description
Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features: Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description: The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What You Will Learn: Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for: Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.
Product Specifications
- Brand
- Packt Publishing
- Format
- paperback
- ASIN
- 178934641X
- Domain
- Amazon UK
- Release Date
- 31 December 2018
- Listed Since
- 19 October 2018
Barcode
No barcode data available
Similar Products You Might Like
97% match
Packt Machine Learning for Algorithmic Trading Python Book
Packt Publishing
£57.45
20 Aug 2026
97% match
Machine Learning for Algorithmic Trading - Second Edition: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python
Packt Publishing
£59.98
23 Sep 2026
97% match
Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python
Packt Publishing
£47.48
21 Aug 2026
96% match
CRC Press Algorithmic Trading and Quantitative Strategies Book
CRC Press
£109.46
17 Oct 2026
96% match
Introduction To Machine Learning In Quantitative Finance, An: 0 (Advanced Textbooks In Mathematics)
Scientific Publishing
£35.90
11 Aug 2026
96% match
Day Trade With AI: Theoretical foundations for discretionary, algorithmic, and diversified trading with AI
£44.17
10 Sep 2026
96% match
Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python
O'Reilly
£45.65
20 Aug 2026
96% match
Machine Learning for Factor Investing: Python Version (Chapman and Hall/CRC Financial Mathematics Series)
Chapman and Hall/CRC
£184.65
08 Oct 2026
96% match
Machine Learning for Factor Investing - R Version Book
CRC Press
£115.00
17 Oct 2026
96% match
Testing and Tuning Market Trading Systems: Algorithms in C++
Apress
£36.79
08 Oct 2026
96% match
Online Portfolio Selection: Principles and Algorithms
CRC Press
£52.24
06 Aug 2026
96% match
Online Portfolio Selection: Principles and Algorithms
CRC Press
£110.00
05 Sep 2026
96% match
Academic Press Algorithmic Trading Methods - 2nd Edition
Academic Press
£71.68
20 Aug 2026
96% match
Springer Machine Learning in Finance - Theory to Practice Book
Springer
£68.31
22 Oct 2026
96% match
Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices
Cambridge University Press
£90.99
26 Sep 2026
96% match
O'Reilly Artificial Intelligence in Finance - Python Guide
O'Reilly
£50.54
20 Aug 2026
96% match
Springer Machine Learning in Finance: Theory to Practice Book
Springer
£51.19
11 Aug 2026
96% match
Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization
£260.84
16 Aug 2026
96% match
Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python
O'Reilly
£39.89
14 Aug 2026
96% match
Wiley Machine Learning and Big Data with kdb+/q Book
Wiley
£58.07
03 Sep 2026
96% match
Wiley Building Winning Algorithmic Trading Systems Book
Wiley
£43.53
20 Aug 2026
96% match
Machine Learning for Factor Investing: R Version (Chapman and Hall/CRC Financial Mathematics Series)
CRC Press
£74.45
25 Sep 2026
96% match
Deep Learning in Quantitative Trading - Cambridge Elements
Cambridge University Press
£49.50
03 Sep 2026
96% match
Data Analytics for Finance Using Python (Advances in Digital Technologies for Smart Applications)
CRC Press
£44.99
08 Sep 2026