From 3d2ffbf971be7081d1416fc7677eb2a141bf6e19 Mon Sep 17 00:00:00 2001 From: Justin Gage Date: Wed, 9 Oct 2019 12:51:43 -0400 Subject: [PATCH 1/4] copy edits --- static/docs/get-started/agenda.md | 54 +++++++++++++++---------------- 1 file changed, 27 insertions(+), 27 deletions(-) diff --git a/static/docs/get-started/agenda.md b/static/docs/get-started/agenda.md index c4adb389f4..0716a6059e 100644 --- a/static/docs/get-started/agenda.md +++ b/static/docs/get-started/agenda.md @@ -1,36 +1,36 @@ -# Agenda +# Agenda -In the next few sections we will build a simple natural language processing -(NLP) project from scratch. If you'd like to get the final result or have some -issues along the way, you can download the fully reproducible -[GitHub project](https://github.com/iterative/example-get-started) with: +In the next few sections we'll build a simple natural language processing (NLP) +project from scratch. If you'd like to get the final result or have any issues +along the way, you can download the fully reproducible +[GitHub project](https://github.com/iterative/example-get-started) by running: ```dvc -$ git clone https://github.com/iterative/example-get-started +$ git clone https://github.com/iterative/example-get-started ``` -Otherwise, bear with us and we will introduce the basic DVC concepts and get to -the same result together! +Otherwise, bear with us and we'll introduce some basic DVC concepts and get to +the same results together! -The idea of the project is a simplified version of the -[Tutorial](/doc/tutorials/deep). It explores the NLP problem of predicting tags -for a given StackOverflow question. For example, we want a classifier that can -predict posts about the Python language by tagging them `python`. +The idea of the project is a simplified version of our +[simple text classification tutorial](/doc/tutorials/deep). It explores the NLP +problem of predicting tags for a given StackOverflow question. For example, +let's say we want a classifier that can identify posts about Python by tagging +them with `python`. ![](/static/img/example-flow-2x.png) -Do not let the NLP nature of the example discourage you from using DVC in other -Data Science areas. There was no strong reason behind picking the NLP area. On -contrary, DVC is designed to be agnostic of frameworks, languages, etc. If you -have data files or datasets and/or you produce other data files, models, -datasets and you want to: - -- Capture and save those data artifacts the same way we capture - code -- Track and switch between different versions of the data easily -- Be able to answer the question of how data artifacts (e.g. ML models) were - built in the first place -- Be able to compare them -- Bring best practices to your team and get everyone on the same page - -Then you are in a good place! Click the `Next` button below to start ↘ +This problem is natural language processing related, but NLP isn't the only Data +Science context that DVC can help with. DVC is designed to be agnostic to +frameworks, languages, and problem sets. If you _have_ data files or datasets +and/or you _produce_ data files, models, or datasets and you want to: + +- Capture and save those data artifacts the same way you capture +  code +- Track and switch between different versions of data easily +- Be able to understand how data artifacts (e.g. ML models) were built in the +  first place +- Be able to compare models to one another +- Bring software best practices to your team and get everyone on the same page + +Then you're in the right place! Click the `Next` button below to start ↘ \ No newline at end of file From 4393fb6d2160d24af0656156ac50745ccf691d0b Mon Sep 17 00:00:00 2001 From: Justin Gage Date: Wed, 9 Oct 2019 13:01:52 -0400 Subject: [PATCH 2/4] Update agenda.md --- static/docs/get-started/agenda.md | 49 +++++++++++++++---------------- 1 file changed, 24 insertions(+), 25 deletions(-) diff --git a/static/docs/get-started/agenda.md b/static/docs/get-started/agenda.md index 0716a6059e..0995f80c68 100644 --- a/static/docs/get-started/agenda.md +++ b/static/docs/get-started/agenda.md @@ -1,36 +1,35 @@ -# Agenda +# Agenda -In the next few sections we'll build a simple natural language processing (NLP) -project from scratch. If you'd like to get the final result or have any issues -along the way, you can download the fully reproducible -[GitHub project](https://github.com/iterative/example-get-started) by running: +In the next few sections we'll build a simple natural language processing (NLP) +project from scratch. If you'd like to get the final result or have any issues +along the way, you can download the fully reproducible +[GitHub project](https://github.com/iterative/example-get-started) by running: ```dvc -$ git clone https://github.com/iterative/example-get-started +$ git clone https://github.com/iterative/example-get-started ``` -Otherwise, bear with us and we'll introduce some basic DVC concepts and get to -the same results together! +Otherwise, bear with us and we'll introduce some basic DVC concepts to get to +the same result together! -The idea of the project is a simplified version of our -[simple text classification tutorial](/doc/tutorials/deep). It explores the NLP -problem of predicting tags for a given StackOverflow question. For example, -let's say we want a classifier that can identify posts about Python by tagging -them with `python`. +The idea of the project is a simplified version of our +[text classification tutorial](/doc/tutorials/deep). It explores the NLP problem +of predicting tags for a given StackOverflow question. For example, we might +want a classifier that can flag (or predict) posts about Python by tagging them +with `python`. ![](/static/img/example-flow-2x.png) -This problem is natural language processing related, but NLP isn't the only Data -Science context that DVC can help with. DVC is designed to be agnostic to -frameworks, languages, and problem sets. If you _have_ data files or datasets -and/or you _produce_ data files, models, or datasets and you want to: +This is a natural language processing context, but NLP isn't the only area where +DVC can help. DVC is designed to be agnostic of frameworks, languages, etc. If +you _have_ data files or datasets and/or you _produce_ data files, models, or +datasets and you want to: -- Capture and save those data artifacts the same way you capture -  code -- Track and switch between different versions of data easily -- Be able to understand how data artifacts (e.g. ML models) were built in the -  first place -- Be able to compare models to one another -- Bring software best practices to your team and get everyone on the same page +- Capture and save those data artifacts the same way you capture + code +- Track and switch between different versions of data easily +- Understand how data artifacts (e.g. ML models) were built in the first place +- Be able to compare models to each other +- Bring software best practices to your team and get everyone on the same page -Then you're in the right place! Click the `Next` button below to start ↘ \ No newline at end of file +Then you're in the right place! Click the `Next` button below to start ↘ From eb6b1072e8e29a298a40a689ae22a1111e1a4d0f Mon Sep 17 00:00:00 2001 From: Justin Gage Date: Wed, 9 Oct 2019 14:02:03 -0400 Subject: [PATCH 3/4] copy edits v2 --- static/docs/get-started/agenda.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/static/docs/get-started/agenda.md b/static/docs/get-started/agenda.md index 0995f80c68..19a6ff1606 100644 --- a/static/docs/get-started/agenda.md +++ b/static/docs/get-started/agenda.md @@ -13,17 +13,17 @@ Otherwise, bear with us and we'll introduce some basic DVC concepts to get to the same result together! The idea of the project is a simplified version of our -[text classification tutorial](/doc/tutorials/deep). It explores the NLP problem -of predicting tags for a given StackOverflow question. For example, we might -want a classifier that can flag (or predict) posts about Python by tagging them +[Deep Dive Tutorial](/doc/tutorials/deep). It explores the NLP problem of +predicting tags for a given StackOverflow question. For example, we might want a +classifier that can classify (or predict) posts about Python by tagging them with `python`. ![](/static/img/example-flow-2x.png) -This is a natural language processing context, but NLP isn't the only area where -DVC can help. DVC is designed to be agnostic of frameworks, languages, etc. If -you _have_ data files or datasets and/or you _produce_ data files, models, or -datasets and you want to: +This is a natural language processing context, but NLP isn't the only area of +data science where DVC can help. DVC is designed to be agnostic of frameworks, +languages, etc. If you have data files or datasets and/or you produce data +files, models, or datasets and you want to: - Capture and save those data artifacts the same way you capture code From 00ef5d7d1901e9ef06d2ce9f58cfc891cd330ca1 Mon Sep 17 00:00:00 2001 From: Justin Gage Date: Wed, 9 Oct 2019 14:53:32 -0400 Subject: [PATCH 4/4] changed results copy --- static/docs/get-started/agenda.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/static/docs/get-started/agenda.md b/static/docs/get-started/agenda.md index 19a6ff1606..2ef97bb9ee 100644 --- a/static/docs/get-started/agenda.md +++ b/static/docs/get-started/agenda.md @@ -9,8 +9,8 @@ along the way, you can download the fully reproducible $ git clone https://github.com/iterative/example-get-started ``` -Otherwise, bear with us and we'll introduce some basic DVC concepts to get to -the same result together! +Otherwise, bear with us and we'll introduce some basic DVC concepts to get the +same results together! The idea of the project is a simplified version of our [Deep Dive Tutorial](/doc/tutorials/deep). It explores the NLP problem of