Algorithmia update

Author: besirkurtulmus

README.md

@@ -233,18 +233,6 @@ IPython Notebook(s) demonstrating Hadoop MapReduce with mrjob functionality.
 
 <br/>
 
-<p align="center">
-  <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/algorithmia.png">
-</p>
-
-## 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. |
-
 <p align="center">
   <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/aws.png">
 </p>
@@ -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
 

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,