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Commit a24ff338 authored by Warris, Sven's avatar Warris, Sven
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typos

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......@@ -41,7 +41,7 @@ Big data is everywhere:
* Physics
+ Large Hadron Collider: 30 Petabytes / year
* Social Media
+ Facebook / Youtube / Intagram
+ Facebook / Youtube / Instagram
* Life sciences
+ Illumina NovaSeq: 4TB / run
+ National Plant Eco-phenotyping Center (NPEC): 2-3 TB / day
......@@ -176,6 +176,7 @@ Basic idea:
- Did somebody else solve this problem?
- Wikipedia
- books on algorithms and data structures
- ask ChatGPT
- Implement other way of processing data
- Works in all programming languages
- With growing experience / knowledge comes better design
......@@ -419,7 +420,7 @@ distributions <- parLapply(cl, nList,
# Parallel programming
* Otherway of thinking
* Other way of thinking
* Understand the problem
* Determine whether or not the problem is one that can
actually be parallelized
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......@@ -188,7 +188,7 @@ ggplot(capsicumPhenotypes, aes(x=greenness_aver)) + geom_histogram(binwidth=500,
## Classification, training & test set:
```{r echo=TRUE, warning=FALSE, message=FALSE, tidy=TRUE}
```{r echo=TRUE, warning=FALSE, message=FALSE, tidy=FALSE}
set.seed(123)
capsicumPhenotypes <-
......@@ -209,7 +209,7 @@ test <- capsicumPhenotypes[-s,]
## Phenotype vs variables
```{r echo=TRUE, warning=FALSE, message=FALSE, library(formatR), tidy=TRUE, fig.height=5}
```{r echo=TRUE, warning=FALSE, message=FALSE, library(formatR), tidy=FALSE, fig.height=5}
ggpairs(capsicumPhenotypes[capsicumPhenotypes[,15]==
c('cgn16951','sweet banana','Tequila'),],
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