From 632d9ff4382469f4db50deb25c154f39ca9e56dd Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Tue, 6 Aug 2024 11:58:38 +0200
Subject: [PATCH 01/14] add announcements CZI EOSS6

---
 _posts/2024-08-06-czi-eoss6-announcement.md   |  21 ++++++++++++++++++
 .../author_images/guillaume-lemaitre.jpg      | Bin 0 -> 6033 bytes
 assets/images/posts_images/sklearn_czi.png    | Bin 0 -> 30996 bytes
 3 files changed, 21 insertions(+)
 create mode 100644 _posts/2024-08-06-czi-eoss6-announcement.md
 create mode 100644 assets/images/author_images/guillaume-lemaitre.jpg
 create mode 100644 assets/images/posts_images/sklearn_czi.png

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
new file mode 100644
index 0000000..d1858c2
--- /dev/null
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -0,0 +1,21 @@
+---
+title: "Scikit-learn awarded CZI EOSS Cycle 6 Grant"
+date: August 6, 2024
+categories:
+  - Funding
+tags:
+  - Open Source
+  - Sponsor
+  - Internship
+  - Diversity
+featured-image: sklearn_czi.png
+
+postauthors:
+  - name: Guillaume Lemaitre
+    website: https://glemaitre.github.io/
+    image: guillaume-lemaitre.jpg
+---
+<div>
+  <img src="/assets/images/posts_images/{{ page.featured-image }}" alt="">
+  {% include postauthor.html %}
+</div>
\ No newline at end of file
diff --git a/assets/images/author_images/guillaume-lemaitre.jpg b/assets/images/author_images/guillaume-lemaitre.jpg
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literal 0
HcmV?d00001


From d3dcc4b5726bc6731ba3c647271f45f7e02fff34 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Wed, 7 Aug 2024 09:18:30 +0200
Subject: [PATCH 02/14] Update _posts/2024-08-06-czi-eoss6-announcement.md

Co-authored-by: Reshama Shaikh <reshama.stat@gmail.com>
---
 _posts/2024-08-06-czi-eoss6-announcement.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index d1858c2..9da7c7c 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -5,7 +5,7 @@ categories:
   - Funding
 tags:
   - Open Source
-  - Sponsor
+  - Funding
   - Internship
   - Diversity
 featured-image: sklearn_czi.png

From c77cf1c6cc62f096d6161d7f0c081ea87fb419f4 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Wed, 7 Aug 2024 15:51:53 +0200
Subject: [PATCH 03/14] more draft

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 73 ++++++++++++++++++++-
 1 file changed, 72 insertions(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 9da7c7c..d716d82 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -18,4 +18,75 @@ postauthors:
 <div>
   <img src="/assets/images/posts_images/{{ page.featured-image }}" alt="">
   {% include postauthor.html %}
-</div>
\ No newline at end of file
+</div>
+
+We are delighted to announce that `scikit-learn` is awarded a grant from
+the [Chan Zuckerberg Initiative (CZI)](https://chanzuckerberg.com/)'s [Essential Open
+Source Software for Science
+(EOSS)](https://chanzuckerberg.com/rfa/essential-open-source-software-for-science/)
+program. This grant is funded by [Wellcome Trust](https://wellcome.org/).
+As in previous round, this cycle supports open-source software projects that are
+essential to biomedical research. This is the third time that CZI EOSS supports
+`scikit-learn`. In previous rounds, the following projects were funded:
+
+- [CZI EOSS 1](https://chanzuckerberg.com/eoss/proposals/scikit-learn-maintenance-and-enhancement-for-gradient-boosting/)
+  helped at creating to the
+  [`HistGradientBoostingClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html) and
+  [`HistGradientBoostingRegressor`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html) estimators.
+  These estimators are the equivalent of gradient boosting models implemented in
+  `LightGBM` and `XGBoost`.
+- [CZI EOSS 4](https://chanzuckerberg.com/eoss/proposals/maintenance-extension-of-scikit-learn-machine-learning-in-python/)
+  extended `scikit-learn` to work better with missing values and categorical data in
+  several estimators.
+
+Both grants allowed us to maintain and enhance `scikit-learn` to better serve the
+community.
+
+In this new grant, we will focus on improving the evaluation and inspection of
+predictive models. We provide in the next section a detailed description of the
+proposed work.
+
+## Predictive models evaluation & inspection
+
+When building a machine learning pipeline for a specific research problem, two key
+aspects are closely connected: (i) design the pipeline and (ii) assess, analyze, and
+inspect it. Researchers strive to identify the optimal pipeline, maximizing specific
+evaluation metrics, while also seeking at explaining the validity and rationale behind
+the pipeline's predictions. This is the corner stone to properly answering research
+questions. With this proposal we aim to improve and extend the available `scikit-learn`
+tools.
+
+`scikit-learn` provides building blocks for model evaluation and statistical analysis of
+results. Originally, this information was presented in a raw format and required
+expertise from scientists to create intuitive supports for outreach to peers and
+outsiders. Recently, the `scikit-learn` community developed displays to easily generate
+visual figures for communicating such results. However, these displays are still in
+their early development stages and do not leverage all available statistical analysis
+tools (i.e., cross-validation) from `scikit-learn`. Thus, we aim to expand these
+displays to use the right statistical tools and thus promote the adoption of best
+practices when reporting results. Additionally, we also intend to create new displays
+that are considered as "standards" during such analyses.
+
+In the domain of model inspection, we aim to address several areas: (i) model inspection
+during training, (ii) enhancing user experience through interactive inspection, and
+(iii) model explainability. First, during the training of a pipeline, researchers are
+interested in monitoring the internal characteristics of the model and it is a not yet
+addressed long-standing issue in `scikit-learn`. We want to build upon some initial work
+by implementing a "callback" framework that allows users to track these internal
+parameters. Next, researchers commonly use interactive tools such as Jupyter Notebook to
+develop pipelines. `scikit-learn` started some efforts to visually and interactively
+display pipelines in these environments. However, there is room for improvement in terms
+of user interaction and accessibility. Finally, as `scikit-learn` is widely used as a
+reference package, it is crucial to improve the section of the library dedicated to
+model explainability. We aim to improve the documentation and user experience with the
+existing explainability tools, making sure that they use the appropriate tool for their
+use cases.
+
+On top of all these items, we intend to continue working on the general maintenance of
+the project, addressing bug reports and performance regressions. As a community-driven
+project, we want to dedicate time reviewing external contributions.
+
+## References
+
+[1] [Scikit-learn proposal for CZI EOSS
+6](https://github.com/scikit-learn/administrative/blob/master/czi_eoss_proposal/EOSS6-0000000551_202312181059.pdf)

From 7db29a5e055c4b8d4743fe9fe47c341484afb8b8 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 09:19:42 +0200
Subject: [PATCH 04/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 22 ++++++++++++++++++---
 1 file changed, 19 insertions(+), 3 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index d716d82..a79abfd 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -12,8 +12,11 @@ featured-image: sklearn_czi.png
 
 postauthors:
   - name: Guillaume Lemaitre
-    website: https://glemaitre.github.io/
+    website: https://github.com/glemaitre
     image: guillaume-lemaitre.jpg
+  - name: Lucy Liu
+    website: https://github.com/lucyleeow
+    image: lucyliu.jpeg
 ---
 <div>
   <img src="/assets/images/posts_images/{{ page.featured-image }}" alt="">
@@ -44,7 +47,7 @@ community.
 
 In this new grant, we will focus on improving the evaluation and inspection of
 predictive models. We provide in the next section a detailed description of the
-proposed work.
+proposed work. One can find the full submitted proposal in [1].
 
 ## Predictive models evaluation & inspection
 
@@ -84,7 +87,20 @@ use cases.
 
 On top of all these items, we intend to continue working on the general maintenance of
 the project, addressing bug reports and performance regressions. As a community-driven
-project, we want to dedicate time reviewing external contributions.
+project, we want to dedicate time reviewing external contributions.\
+
+## Involved people
+
+To execute this project, we plan the following hires:
+
+- [Lucy Liu](https://github.com/lucyleeow) (Quansight Labs) will work about half-time on
+  the project, on topic related to displays and feature importance.
+- We will hire full-time internships to work on the other part of the project. The
+  initial plan is to hire two interns for a period of 6 months each and repeat this
+  process for the next 2 years. We want to provide opportunities to underrepresented
+  groups in the field of machine learning and data science, similarly to previous
+  initiatives (cf. [NumFOCUS Small Development
+  Grant](https://blog.scikit-learn.org/diversity/mentoring/)).
 
 ## References
 

From ac99c7eb7d5544f49c8322faf1cd96cf676d7989 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 09:59:43 +0200
Subject: [PATCH 05/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 7 +------
 1 file changed, 1 insertion(+), 6 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index a79abfd..2906d6c 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -47,7 +47,7 @@ community.
 
 In this new grant, we will focus on improving the evaluation and inspection of
 predictive models. We provide in the next section a detailed description of the
-proposed work. One can find the full submitted proposal in [1].
+proposed work.
 
 ## Predictive models evaluation & inspection
 
@@ -101,8 +101,3 @@ To execute this project, we plan the following hires:
   groups in the field of machine learning and data science, similarly to previous
   initiatives (cf. [NumFOCUS Small Development
   Grant](https://blog.scikit-learn.org/diversity/mentoring/)).
-
-## References
-
-[1] [Scikit-learn proposal for CZI EOSS
-6](https://github.com/scikit-learn/administrative/blob/master/czi_eoss_proposal/EOSS6-0000000551_202312181059.pdf)

From d1e982c7af46ff46690818670b5b265465d66fc5 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 10:05:48 +0200
Subject: [PATCH 06/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 2906d6c..e449678 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -1,5 +1,5 @@
 ---
-title: "Scikit-learn awarded CZI EOSS Cycle 6 Grant"
+title: "Chan Zuckerberg Initiative considers scikit-learn an Essential Open Source Software"
 date: August 6, 2024
 categories:
   - Funding

From d87d7996d3456deed0cc6bc53100e30d4027bb5e Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 10:35:10 +0200
Subject: [PATCH 07/14] Update _posts/2024-08-06-czi-eoss6-announcement.md

Co-authored-by: Tim Head <betatim@gmail.com>
---
 _posts/2024-08-06-czi-eoss6-announcement.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index e449678..7882d08 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -23,7 +23,7 @@ postauthors:
   {% include postauthor.html %}
 </div>
 
-We are delighted to announce that `scikit-learn` is awarded a grant from
+We are delighted to announce that `scikit-learn` has been awarded a grant from
 the [Chan Zuckerberg Initiative (CZI)](https://chanzuckerberg.com/)'s [Essential Open
 Source Software for Science
 (EOSS)](https://chanzuckerberg.com/rfa/essential-open-source-software-for-science/)

From f37acf4a3ecb3158eba545fd6379ba0b462614cc Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 10:36:31 +0200
Subject: [PATCH 08/14] Apply suggestions from code review

Co-authored-by: Tim Head <betatim@gmail.com>
---
 _posts/2024-08-06-czi-eoss6-announcement.md | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 7882d08..0c8a608 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -28,25 +28,25 @@ the [Chan Zuckerberg Initiative (CZI)](https://chanzuckerberg.com/)'s [Essential
 Source Software for Science
 (EOSS)](https://chanzuckerberg.com/rfa/essential-open-source-software-for-science/)
 program. This grant is funded by [Wellcome Trust](https://wellcome.org/).
-As in previous round, this cycle supports open-source software projects that are
+As in previous rounds, this cycle supports open-source software projects that are
 essential to biomedical research. This is the third time that CZI EOSS supports
 `scikit-learn`. In previous rounds, the following projects were funded:
 
 - [CZI EOSS 1](https://chanzuckerberg.com/eoss/proposals/scikit-learn-maintenance-and-enhancement-for-gradient-boosting/)
-  helped at creating to the
+  helped create the
   [`HistGradientBoostingClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html) and
   [`HistGradientBoostingRegressor`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html) estimators.
   These estimators are the equivalent of gradient boosting models implemented in
   `LightGBM` and `XGBoost`.
 - [CZI EOSS 4](https://chanzuckerberg.com/eoss/proposals/maintenance-extension-of-scikit-learn-machine-learning-in-python/)
-  extended `scikit-learn` to work better with missing values and categorical data in
+  extended `scikit-learn` to improve handling of missing values and categorical data in
   several estimators.
 
 Both grants allowed us to maintain and enhance `scikit-learn` to better serve the
 community.
 
 In this new grant, we will focus on improving the evaluation and inspection of
-predictive models. We provide in the next section a detailed description of the
+predictive models. In the next section we will describe the
 proposed work.
 
 ## Predictive models evaluation & inspection
@@ -55,13 +55,13 @@ When building a machine learning pipeline for a specific research problem, two k
 aspects are closely connected: (i) design the pipeline and (ii) assess, analyze, and
 inspect it. Researchers strive to identify the optimal pipeline, maximizing specific
 evaluation metrics, while also seeking at explaining the validity and rationale behind
-the pipeline's predictions. This is the corner stone to properly answering research
+the pipeline's predictions. This is the cornerstone of answering research
 questions. With this proposal we aim to improve and extend the available `scikit-learn`
 tools.
 
 `scikit-learn` provides building blocks for model evaluation and statistical analysis of
 results. Originally, this information was presented in a raw format and required
-expertise from scientists to create intuitive supports for outreach to peers and
+expertise from scientists to create intuitive reports for outreach to peers and
 outsiders. Recently, the `scikit-learn` community developed displays to easily generate
 visual figures for communicating such results. However, these displays are still in
 their early development stages and do not leverage all available statistical analysis
@@ -87,7 +87,7 @@ use cases.
 
 On top of all these items, we intend to continue working on the general maintenance of
 the project, addressing bug reports and performance regressions. As a community-driven
-project, we want to dedicate time reviewing external contributions.\
+project, we want to dedicate time reviewing external contributions.
 
 ## Involved people
 

From 5eea197f2eac28523634257e7a022c68f893ff66 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 10:36:41 +0200
Subject: [PATCH 09/14] Update _posts/2024-08-06-czi-eoss6-announcement.md

Co-authored-by: Tim Head <betatim@gmail.com>
---
 _posts/2024-08-06-czi-eoss6-announcement.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 0c8a608..8229e01 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -36,7 +36,7 @@ essential to biomedical research. This is the third time that CZI EOSS supports
   helped create the
   [`HistGradientBoostingClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html) and
   [`HistGradientBoostingRegressor`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html) estimators.
-  These estimators are the equivalent of gradient boosting models implemented in
+  These estimators are equivalent to the gradient boosting models implemented in
   `LightGBM` and `XGBoost`.
 - [CZI EOSS 4](https://chanzuckerberg.com/eoss/proposals/maintenance-extension-of-scikit-learn-machine-learning-in-python/)
   extended `scikit-learn` to improve handling of missing values and categorical data in

From 5cd313bab5c9a8f113c7830bea7b6b7fd3dc605e Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Thu, 8 Aug 2024 10:44:27 +0200
Subject: [PATCH 10/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 35 +++++++++++----------
 1 file changed, 19 insertions(+), 16 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 8229e01..096a03f 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -30,24 +30,10 @@ Source Software for Science
 program. This grant is funded by [Wellcome Trust](https://wellcome.org/).
 As in previous rounds, this cycle supports open-source software projects that are
 essential to biomedical research. This is the third time that CZI EOSS supports
-`scikit-learn`. In previous rounds, the following projects were funded:
-
-- [CZI EOSS 1](https://chanzuckerberg.com/eoss/proposals/scikit-learn-maintenance-and-enhancement-for-gradient-boosting/)
-  helped create the
-  [`HistGradientBoostingClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html) and
-  [`HistGradientBoostingRegressor`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html) estimators.
-  These estimators are equivalent to the gradient boosting models implemented in
-  `LightGBM` and `XGBoost`.
-- [CZI EOSS 4](https://chanzuckerberg.com/eoss/proposals/maintenance-extension-of-scikit-learn-machine-learning-in-python/)
-  extended `scikit-learn` to improve handling of missing values and categorical data in
-  several estimators.
-
-Both grants allowed us to maintain and enhance `scikit-learn` to better serve the
-community.
+`scikit-learn`.
 
 In this new grant, we will focus on improving the evaluation and inspection of
-predictive models. In the next section we will describe the
-proposed work.
+predictive models.
 
 ## Predictive models evaluation & inspection
 
@@ -101,3 +87,20 @@ To execute this project, we plan the following hires:
   groups in the field of machine learning and data science, similarly to previous
   initiatives (cf. [NumFOCUS Small Development
   Grant](https://blog.scikit-learn.org/diversity/mentoring/)).
+
+## Past CZI EOSS grants
+
+In the past `scikit-learn` has been awarded two grants from the CZI EOSS program:
+
+- [CZI EOSS Cycle 1](https://chanzuckerberg.com/eoss/proposals/scikit-learn-maintenance-and-enhancement-for-gradient-boosting/)
+  helped at creating to the
+  [`HistGradientBoostingClassifier`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html) and
+  [`HistGradientBoostingRegressor`](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html) estimators.
+  These estimators are the equivalent of gradient boosting models implemented in
+  `LightGBM` and `XGBoost`.
+- [CZI EOSS Cycle 4](https://chanzuckerberg.com/eoss/proposals/maintenance-extension-of-scikit-learn-machine-learning-in-python/)
+  extended `scikit-learn` to work better with missing values and categorical data in
+  several estimators.
+
+Both grants allowed us to maintain and enhance `scikit-learn` to better serve the
+community.

From d63f8239bbecba7da5df4b3d317c2bb858a1f5bc Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Fri, 9 Aug 2024 09:35:45 +0200
Subject: [PATCH 11/14] Apply suggestions from code review

Co-authored-by: Lucy Liu <jliu176@gmail.com>
---
 _posts/2024-08-06-czi-eoss6-announcement.md | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 096a03f..2d3d462 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -38,8 +38,8 @@ predictive models.
 ## Predictive models evaluation & inspection
 
 When building a machine learning pipeline for a specific research problem, two key
-aspects are closely connected: (i) design the pipeline and (ii) assess, analyze, and
-inspect it. Researchers strive to identify the optimal pipeline, maximizing specific
+aspects are closely connected: (i) design of the pipeline and (ii) assessment, analysis, and
+inspection of it. Researchers strive to identify the optimal pipeline, maximizing specific
 evaluation metrics, while also seeking at explaining the validity and rationale behind
 the pipeline's predictions. This is the cornerstone of answering research
 questions. With this proposal we aim to improve and extend the available `scikit-learn`
@@ -52,14 +52,14 @@ outsiders. Recently, the `scikit-learn` community developed displays to easily g
 visual figures for communicating such results. However, these displays are still in
 their early development stages and do not leverage all available statistical analysis
 tools (i.e., cross-validation) from `scikit-learn`. Thus, we aim to expand these
-displays to use the right statistical tools and thus promote the adoption of best
+displays, using the right statistical tools and thus promote the adoption of best
 practices when reporting results. Additionally, we also intend to create new displays
 that are considered as "standards" during such analyses.
 
 In the domain of model inspection, we aim to address several areas: (i) model inspection
 during training, (ii) enhancing user experience through interactive inspection, and
 (iii) model explainability. First, during the training of a pipeline, researchers are
-interested in monitoring the internal characteristics of the model and it is a not yet
+interested in monitoring the internal characteristics of the model, which is a not yet
 addressed long-standing issue in `scikit-learn`. We want to build upon some initial work
 by implementing a "callback" framework that allows users to track these internal
 parameters. Next, researchers commonly use interactive tools such as Jupyter Notebook to
@@ -73,7 +73,7 @@ use cases.
 
 On top of all these items, we intend to continue working on the general maintenance of
 the project, addressing bug reports and performance regressions. As a community-driven
-project, we want to dedicate time reviewing external contributions.
+project, we also want to dedicate time reviewing external contributions.
 
 ## Involved people
 

From 1e1bd912c77047864630bbbe015912a4d7e7bae1 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Fri, 9 Aug 2024 09:52:45 +0200
Subject: [PATCH 12/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 2d3d462..3d75094 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -32,8 +32,9 @@ As in previous rounds, this cycle supports open-source software projects that ar
 essential to biomedical research. This is the third time that CZI EOSS supports
 `scikit-learn`.
 
-In this new grant, we will focus on improving the evaluation and inspection of
-predictive models.
+In this new grant, we will focus on improving the [evaluation and inspection of
+predictive
+models](https://chanzuckerberg.com/eoss/proposals/predictive-models-evaluation-inspection-in-scikit-learn/).
 
 ## Predictive models evaluation & inspection
 

From 5f2a96c899206701ac0c6f7dc6701e13990dbb07 Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Fri, 9 Aug 2024 10:02:42 +0200
Subject: [PATCH 13/14] iter

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index 3d75094..ccf65ad 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -55,7 +55,7 @@ their early development stages and do not leverage all available statistical ana
 tools (i.e., cross-validation) from `scikit-learn`. Thus, we aim to expand these
 displays, using the right statistical tools and thus promote the adoption of best
 practices when reporting results. Additionally, we also intend to create new displays
-that are considered as "standards" during such analyses.
+to support common analysis tasks that are not yet covered in `scikit-learn`.
 
 In the domain of model inspection, we aim to address several areas: (i) model inspection
 during training, (ii) enhancing user experience through interactive inspection, and

From ddcdeca53a1f3e9d959946da2118635d82a4641e Mon Sep 17 00:00:00 2001
From: Guillaume Lemaitre <guillaume@probabl.ai>
Date: Tue, 27 Aug 2024 10:19:24 +0200
Subject: [PATCH 14/14] add point raised by Lucy

---
 _posts/2024-08-06-czi-eoss6-announcement.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/_posts/2024-08-06-czi-eoss6-announcement.md b/_posts/2024-08-06-czi-eoss6-announcement.md
index ccf65ad..0dacc86 100644
--- a/_posts/2024-08-06-czi-eoss6-announcement.md
+++ b/_posts/2024-08-06-czi-eoss6-announcement.md
@@ -70,7 +70,10 @@ of user interaction and accessibility. Finally, as `scikit-learn` is widely used
 reference package, it is crucial to improve the section of the library dedicated to
 model explainability. We aim to improve the documentation and user experience with the
 existing explainability tools, making sure that they use the appropriate tool for their
-use cases.
+use cases. In addition, we propose to work on a scikit-learn enhancement proposal (SLEP)
+to define a common API for model explainability within scikit-learn. Ultimately, the
+goal is to come to a consensus to provide scikit-learn end-users with a consistent
+experience when using model explainability tools.
 
 On top of all these items, we intend to continue working on the general maintenance of
 the project, addressing bug reports and performance regressions. As a community-driven