From ea4588ad82fa1e99edb19d9ce3074cea98fb3724 Mon Sep 17 00:00:00 2001 From: "A. Besir Kurtulmus" Date: Mon, 18 Jan 2016 17:08:06 +0200 Subject: [PATCH] Algorithmia update --- README.md | 13 +--------- algorithmia/Algorithmia.ipynb | 45 ++++++++++++++++++++++++++--------- 2 files changed, 35 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 812e84a..38497ab 100644 --- a/README.md +++ b/README.md @@ -233,18 +233,6 @@ IPython Notebook(s) demonstrating Hadoop MapReduce with mrjob functionality.
-

- -

- -## algorithmia - -IPython Notebook(s) demonstrating using Machine Learning, Computer Vision and NLP algorithms. - -| Notebook | Description | -|------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| [Simple Usage](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/algorithmia/Algorithmia.ipynb) | Algorithmia is a marketplace for algorithms. This notebook showcases 4 different algorithms: Face Detection, Content Summarizer, Latent Dirichlet Allocation and Optical Character Recognition. | -

@@ -295,6 +283,7 @@ IPython Notebook(s) demonstrating miscellaneous functionality. | Notebook | Description | |--------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | [regex](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/misc/regex.ipynb) | Regular expression cheat sheet useful in data wrangling.| +[Algorithmia Examples](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/algorithmia/Algorithmia.ipynb) | Algorithmia is a marketplace for algorithms. This notebook showcases 4 different algorithms: Face Detection, Content Summarizer, Latent Dirichlet Allocation and Optical Character Recognition.| ## notebook-installation diff --git a/algorithmia/Algorithmia.ipynb b/algorithmia/Algorithmia.ipynb index 3a5a638..5556fc4 100644 --- a/algorithmia/Algorithmia.ipynb +++ b/algorithmia/Algorithmia.ipynb @@ -16,11 +16,34 @@ "Reference: [Algorithmia Documentation](http://docs.algorithmia.com/)\n", "\n", "Table of Contents:\n", - "1. Authentication\n", - "2. Face Detection\n", - "3. Content Summarizer\n", - "4. Latent Dirichlet Allocation\n", - "5. Optical Character Recognition" + "1. Installation\n", + "2. Authentication\n", + "3. Face Detection\n", + "4. Content Summarizer\n", + "5. Latent Dirichlet Allocation\n", + "6. Optical Character Recognition" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 1. Installation\n", + "\n", + "You need to have the `algorithmia` package (version 0.9.3) installed for this notebook.\n", + "\n", + "You can install the package using the pip package manager:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "pip install algorithmia==0.9.3" ] }, { @@ -41,7 +64,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 1. Authentication\n", + "# 2. Authentication\n", "\n", "You only need your Algorithmia API Key to run the following commands." ] @@ -63,7 +86,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 2. Face Detection\n", + "# 3. Face Detection\n", "\n", "Uses a pretrained model to detect faces in a given image.\n", "\n", @@ -167,7 +190,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 3. Content Summarizer\n", + "# 4. Content Summarizer\n", "\n", "SummarAI is an advanced content summarizer with the option of generating context-controlled summaries. It is based on award-winning patented methods related to artificial intelligence and vector space developed at Lawrence Berkeley National Laboratory." ] @@ -225,7 +248,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 4. Latent Dirichlet Allocation\n", + "# 5. Latent Dirichlet Allocation\n", "\n", "This algorithm takes a group of documents (anything that is made of up text), and returns a number of topics (which are made up of a number of words) most relevant to these documents.\n", "\n", @@ -325,7 +348,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 5. Optical Character Recognition\n", + "# 6. Optical Character Recognition\n", "\n", "Recognize text in your images.\n", "\n", @@ -416,7 +439,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", - "version": "2.7.10" + "version": "2.7.11" } }, "nbformat": 4,