开源软件名称(OpenSource Name):PacktPublishing/Python-Real-World-Machine-Learning
开源软件地址(OpenSource Url):https://github.com/PacktPublishing/Python-Real-World-Machine-Learning
开源编程语言(OpenSource Language):
Jupyter Notebook
93.0%
开源软件介绍(OpenSource Introduction):Python: Real World Machine Learning
Code repository for Python: Real World Machine Learning
##What You Will Learn:
- Use predictive modeling and apply it to real-world problems
- Understand how to perform market segmentation using unsupervised learning
- Apply your new found skills to solve real problems, through clearly-explained code for every technique and test
- Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms
- Increase predictive accuracy with deep learning and scalable data-handling techniques
- Work with modern state-of-the-art large-scale machine learning techniques
Software and Hardware (Module 1):
Chapter number |
Software required (with version) |
Download links to the software |
Hardware specifications |
OS required |
All |
Scikit-learn 0.17.0, Numpy 1.11, Matplotlib 1.5.1, Scipy 0.17.0 |
http://scikit-learn.org/stable/install.html, http://www.scipy.org/scipylib/download.html, http://matplotlib.org/downloads.html, http://www.scipy.org/install.html |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
6 |
NLTK 3.0, Gensim 0.12.4 |
http://www.nltk.org/install.html, https://radimrehurek.com/gensim/install.html |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
7, 8 |
hmmlearn 0.2.1, python_speech_features |
http://hmmlearn.readthedocs.org/en/latest/, http://pythonspeechfeatures.readthedocs.org/en/latest/ |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
8 |
Pandas 0.18.0, Pystruct 0.2.4 |
http://pandas.pydata.org/getpandas.html, https://pystruct.github.io/installation.html |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
9, 10 |
OpenCV 3.0.0 |
http://opencv.org/downloads.html |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
11 |
NeuroLab 0.3.5 |
https://pythonhosted.org/neurolab/install.html |
4 GB of RAM and 16GB of disk |
Linux, Mac OS X, Windows |
Software and Hardware (Module 2):
Chapter number |
Software required (with version) |
1 |
Python 3 (3.4 recommended), sklearn (numpy, scipy), matplotlib |
2-4 |
Theano |
5 |
Semisup-learn |
6 |
Natural Language Toolkit (NLTK), BeautifulSoup |
7 |
Twitter API account |
8 |
XGBoost |
9 |
Lasagne, TensorFlow |
###Note
Modules 1, 2 and 3 have code arranged by chapter (for the chapters that have code). Click here if you have any feedback or suggestions.
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