Update colors etc

3 files changed, 55 insertions, 67 deletions

diff --git a/content/_index.md b/content/_index.md
index c57b808..7fbe911 100644
--- a/content/_index.md
+++ b/content/_index.md
@@ -1,6 +1,6 @@
 ---
 title: "Gustaf Rydholm's Webpage"
-description: "tbc"
+description: "Landing Page"
 ---
 
 ## Introduction
@@ -14,6 +14,7 @@ book reviews/notes, cv, and digital contact information.
 ### On this website...
 
 - [Projects](/projects)
+- [Notes](/notes)
 - [CV](/cv)
 - [Contact](/contact)
 
diff --git a/content/cv.md b/content/cv.md
index bf01d14..812cbf8 100644
--- a/content/cv.md
+++ b/content/cv.md
@@ -134,51 +134,50 @@ tbc...
   *Keywords: Microservices, Kubernetes, Infrastructure, Helm, CI/CD, Kotlin,
   Spring, AWS, Terraform*
 
-- Machine Learning Engineer. Saab AB. Aug 2018 -- Aug 2021
-    - Intelligence Application. Aug 2020 -- Aug 2021
-      - Created data mining pipelines for extracting, cleaning, and creating
-      datasets for machine learning models, i.e. train/test sets.
-      - Was a driving force in making the system more asynchronous using
-      message passing between microservices, by deploying and maintaining a
-      Kafka instance. This improve the architecture by allowing multiple
-      services to subscribe to incoming sensor data and process the
-      information, instead of fetching the data from databases in batches.
-      - Developed a modular pipeline for training and evaluating deep learning
-      models with different architectures and/or losses. Automatic extraction
-      of the best model based on user defined metric, ready for serving.
-      - Built and deployed deep learning models for multi-modal trajectory
-      predictions in production.
-      - Took initiative and deployed and maintained a private Python Package
-      Index (PyPI) for all developers. Greatly improving the development
-      workflow, e.g. forcing versioning, and reducing/eliminating cross
-      dependencies between locally developed Python packages.
-      - Developed a graph algorithm for sensor fusion. Deployed it as a
-      microservice listing to incoming sensor data. This enabled more complex
-      pattern analysis in downstream services.
-      - Reduced the docker image size of the Python microservices from ~2 GB
-      to ~73 MB by utilizing multistage builds and alpine base images.
-      - Built pipelines for CI/CD and packages deployment in Tekton.
-      - With my docker images and pipelines we where able to reduce the
-      average build times from ~10-30 minutes down to seconds, mostly thanks
-      to improved caching capabilities.
-
-      *Keywords: Deep Learning, Python, Microservices, Kubernetes,
-      Infrastructure, Helm, CI/CD*
-
-    - Radar Warning Receiver. Aug 2018 -- Aug 2020
-      - Built simulation software for generating realistic signal
-      environments with both radar and/or communication signals. Implemented
-      the most common signal encoding for communications, as well as
-      basic to SOTA radar modulations. This enabled the team to develop and
-      evaluate different machine learning models and ideas.
-      - Researched machine learning models in different stages of the radar
-      warning receiver, with regards to compute and data limitations.
-      - Held in several presentations of machine learning papers in a company
-      reading group.
-      - Shared the knowledge of implementing and using machine learning to
-      multiple business areas within Saab.
-
-      *Keywords: Deep Learning, Signal Processing, Python, VHDL*
+- Machine Learning Engineer (Cyber Security). Saab AB. Aug 2020 -- Aug 2021
+  - Created data mining pipelines for extracting, cleaning, and creating
+  datasets for machine learning models, i.e. train/test sets.
+  - Was a driving force in making the system more asynchronous using
+  message passing between microservices, by deploying and maintaining a
+  Kafka instance. This improve the architecture by allowing multiple
+  services to subscribe to incoming sensor data and process the
+  information, instead of fetching the data from databases in batches.
+  - Developed a modular pipeline for training and evaluating deep learning
+  models with different architectures and/or losses. Automatic extraction
+  of the best model based on user defined metric, ready for serving.
+  - Built and deployed deep learning models for multi-modal trajectory
+  predictions in production.
+  - Took initiative and deployed and maintained a private Python Package
+  Index (PyPI) for all developers. Greatly improving the development
+  workflow, e.g. forcing versioning, and reducing/eliminating cross
+  dependencies between locally developed Python packages.
+  - Developed a graph algorithm for sensor fusion. Deployed it as a
+  microservice listing to incoming sensor data. This enabled more complex
+  pattern analysis in downstream services.
+  - Reduced the docker image size of the Python microservices from ~2 GB
+  to ~73 MB by utilizing multistage builds and alpine base images.
+  - Built pipelines for CI/CD and packages deployment in Tekton.
+  - With my docker images and pipelines we where able to reduce the
+  average build times from ~10-30 minutes down to seconds, mostly thanks
+  to improved caching capabilities.
+
+  *Keywords: Deep Learning, Python, Microservices, Kubernetes,
+  Infrastructure, Helm, CI/CD*
+
+- Machine Learning Engineer (Surveillance). Saab AB. Aug 2018 -- Aug 2020
+  - Built simulation software for generating realistic signal
+  environments with both radar and/or communication signals. Implemented
+  the most common signal encoding for communications, as well as
+  basic to SOTA radar modulations. This enabled the team to develop and
+  evaluate different machine learning models and ideas.
+  - Researched machine learning models in different stages of the radar
+  warning receiver, with regards to compute and data limitations.
+  - Held in several presentations of machine learning papers in a company
+  reading group.
+  - Shared the knowledge of implementing and using machine learning to
+  multiple business areas within Saab.
+
+  *Keywords: Deep Learning, Signal Processing, Python, VHDL*
 
 ### Institutions
 
diff --git a/static/style.css b/static/style.css
index 87b1b38..d2df580 100644
--- a/static/style.css
+++ b/static/style.css
@@ -1,7 +1,7 @@
 body {
-	background: #073642 ;
-	color: brown ;
-	max-width: 950px ;
+	background: #151515 ;
+	color: #E1E1E1 ;
+	max-width: 750px ;
 	margin: auto ;
 	padding: 0 16px ;
 	margin-bottom: 500px ;
@@ -10,23 +10,15 @@ body {
 }
 
 main {
-	max-width: 950px ;
+	max-width: 750px ;
 	margin: auto ;
 }
 
 main > article {
-	background: #EEE8D5 ;
-	color: #151515 ;
+	background: #151515 ;
+	color: #E1E1E1 ;
 	margin-bottom: 0 ;
-	padding-top: 4em ;
-	padding-left: 8em ;
-	padding-right: 8em ;
-	padding-bottom: 4em ;
-	border-color: #1e4e76 ;
-	border-width: 0.25em 0.25em 0.25em .25em ;
-	border-style: solid ;
   text-align: justify;
-	border-radius: 0 ;
 	margin: auto ;
 }
 
@@ -57,20 +49,16 @@ ul {
 
 footer {
 	max-width: 300px ;
-	background: #EEE8D5 ;
+	background: #151515 ;
 	margin-left: auto ;
 	margin-right: auto ;
-	margin-top: -4px ;
+	margin-top: 6px ;
 	text-align: center ;
 	clear: both ;
-	border-color: #1e4e76 ;
-	border-width: 0em 0.25em 0.25em 0.25em ;
-	border-style: solid ;
-	border-radius: 0 0 0 0 ;
 }
 
 code {
-	color: #373737 ;
+	color: #F4BF75 ;
 	overflow-wrap: break-word ;
 	font-size: 10pt ;
 }