|
6 | 6 | "hide_input": false
|
7 | 7 | },
|
8 | 8 | "source": [
|
9 |
| - "# Outlook\n", |
10 |
| - "## Approaching a machine learning problem\n", |
11 |
| - "## Humans in the loop" |
| 9 | + "## Outlook\n", |
| 10 | + "### Approaching a machine learning problem\n", |
| 11 | + "### Humans in the loop" |
12 | 12 | ]
|
13 | 13 | },
|
14 | 14 | {
|
15 | 15 | "cell_type": "markdown",
|
16 | 16 | "metadata": {},
|
17 | 17 | "source": [
|
18 |
| - "## From prototype to production" |
| 18 | + "### From prototype to production" |
19 | 19 | ]
|
20 | 20 | },
|
21 | 21 | {
|
22 | 22 | "cell_type": "markdown",
|
23 | 23 | "metadata": {},
|
24 | 24 | "source": [
|
25 |
| - "## Testing production systems" |
| 25 | + "### Testing production systems" |
26 | 26 | ]
|
27 | 27 | },
|
28 | 28 | {
|
29 | 29 | "cell_type": "markdown",
|
30 | 30 | "metadata": {},
|
31 | 31 | "source": [
|
32 |
| - "## Building your own estimator" |
| 32 | + "### Building your own estimator" |
33 | 33 | ]
|
34 | 34 | },
|
35 | 35 | {
|
|
69 | 69 | "cell_type": "markdown",
|
70 | 70 | "metadata": {},
|
71 | 71 | "source": [
|
72 |
| - "# Where to go from here\n", |
73 |
| - "## Theory\n", |
74 |
| - "## Other machine learning frameworks and packages\n", |
75 |
| - "## Ranking, recommender systems, time series, and other kinds of learning\n", |
76 |
| - "## Probabilistic modeling, inference and probabilistic programming" |
| 72 | + "### Where to go from here\n", |
| 73 | + "#### Theory\n", |
| 74 | + "#### Other machine learning frameworks and packages\n", |
| 75 | + "#### Ranking, recommender systems, time series, and other kinds of learning\n", |
| 76 | + "#### Probabilistic modeling, inference and probabilistic programming" |
77 | 77 | ]
|
78 | 78 | },
|
79 | 79 | {
|
80 | 80 | "cell_type": "markdown",
|
81 | 81 | "metadata": {},
|
82 | 82 | "source": [
|
83 |
| - "## Neural Networks" |
| 83 | + "#### Neural Networks" |
84 | 84 | ]
|
85 | 85 | },
|
86 | 86 | {
|
87 | 87 | "cell_type": "markdown",
|
88 | 88 | "metadata": {},
|
89 | 89 | "source": [
|
90 |
| - "## Scaling to larger datasets" |
| 90 | + "#### Scaling to larger datasets" |
91 | 91 | ]
|
92 | 92 | },
|
93 | 93 | {
|
94 | 94 | "cell_type": "markdown",
|
95 | 95 | "metadata": {},
|
96 | 96 | "source": [
|
97 |
| - "## Honing your skills" |
| 97 | + "#### Honing your skills" |
98 | 98 | ]
|
99 | 99 | },
|
100 | 100 | {
|
101 | 101 | "cell_type": "markdown",
|
102 | 102 | "metadata": {},
|
103 | 103 | "source": [
|
104 |
| - "## Conclusion" |
| 104 | + "#### Conclusion" |
105 | 105 | ]
|
106 | 106 | }
|
107 | 107 | ],
|
108 | 108 | "metadata": {
|
| 109 | + "anaconda-cloud": {}, |
109 | 110 | "kernelspec": {
|
110 |
| - "display_name": "Python 3", |
| 111 | + "display_name": "Python [Root]", |
111 | 112 | "language": "python",
|
112 |
| - "name": "python3" |
| 113 | + "name": "Python [Root]" |
113 | 114 | },
|
114 | 115 | "language_info": {
|
115 | 116 | "codemirror_mode": {
|
|
121 | 122 | "name": "python",
|
122 | 123 | "nbconvert_exporter": "python",
|
123 | 124 | "pygments_lexer": "ipython3",
|
124 |
| - "version": "3.5.1" |
| 125 | + "version": "3.5.2" |
125 | 126 | }
|
126 | 127 | },
|
127 | 128 | "nbformat": 4,
|
|
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