Seagrass absorbs CO2, supports fisheries, protects coastlines & coral reefs. The @UKHO collaborated with scientific partners @JNCC_UK & @clare_fitz to experiment with #datascience to map seagrass from @esa#Sentinel2 imagery https://t.co/A8GmjPnLcI #COP26#seagrass#marineπ±πβ€οΈ
Brilliant! Some seagrass ground truth data collection using Uncrewed Surface Vessel (USVs). A collaboration with @HSurv@PlymUni@DefraGovUK@NaturalEngland@EnvAgency I'd love to see this data accessible for understanding & conservation of UK marine ecosystems #seagrass#marine
Happy to announce this news on the 1st official @UN-recognised #WorldSeagrassDay! π± We'll be continuing work with @PlymUni to enhance our technique of using #USVs to map #seagrass coverage, reducing damage risk & making seagrass data wholly accessible. π± https://t.co/kON2yu37Nv
CoastalDEM is a DEM utilizing neural networks to reduce NASAβs SRTM error. This map of climate risks produced by NGO Climate Central shows flood risk by 2050. Despite improvements to SRTM for this analysis, caution still recommended #flood#risk#map#data https://t.co/cwXVOuB9fF
Most companies suck at setting goals.
But Google, Amazon, and Microsoft figured it out ages ago.
Hereβs their simple but powerful goal-setting framework (that you can use personally too):
Delighted to announce that our 4-yr research on the first pan-Mediterranean spatially-explicit mapping of ππ°π΄πͺπ₯π°π―πͺπ’ π°π€π¦π’π―πͺπ€π’ seagrass beds at 10 m has been provisionally accepted in @FrontMarineSci. Find more info about our EO recipeπhttps://t.co/eHeypG2bWs
&π
The recent IPCC report shows that today the average North American emits 16 tonnes of carbon dioxide each year from fossil fuel use, compared to just 2 tonnes for the average African. Calls to move to clean energy! https://t.co/zSkEJ0vV7k
Day 18 #100DaysOfCode taking my textual data & creating a #networkx graph aka co-occurrence network. Nodes per word with edges between nodes per sentence. Enjoying degree distribution visualisation & EDA on the number of nodes, edges and average degree #python#NLP#networks π€π
Day 16 #100DaysOfCode "Algorithms to live by" by Brian Christian & Tom Griffiths chpt on sorting; scale, "Big O" time, merge sort, sort vs search: "Sorting something you will never search is a complete waste of time. Searching something you never sorted is merely inefficient"π’π¬
Day 15 #100DaysOfCode In NLP pre-processing stopwords ("a", "the") are typically removed (@NLTK_org stopwords) because they have little lexical content. But stopwords could be meaningful for semantic content analysis or stylometry https://t.co/KkXuA7y88P π±it depends on the task
Day 13: #100DaysOfCode using @NLTK_org to split text into sentences and word tokens. Exploring the punkt unsupervised algorithm recognising punctuation such as "Β£1.2 million" & "N.Y." not splitting on the full stops. Finally looking at lemmatisation wordnet package #nlp
Day 12: #100DaysOfCode The biggest news is I submitted my Networks assignment. Today I started learning about NLP text analysis playing with #nltk and @spacy_io. I'm off for a cuppa to celebrate! π«πͺ π₯³
Day 11: #100DaysOfCode Finished community detection using the Louvain algorithm that maximises modularity! Once I found the 2 largest communities in a network I used closeness centrality to identify the geographically most central point i.e. shortest paths #network#science ππΊοΈ
Day 10: #100DaysOfCode Reading more on community detection https://t.co/JWxYivdYpg and using algorithms from python-igraph @igraph2 π― I am checking modularity to confirm optimal partitions #network#science#clustering
Day 9: #100DaysOfCode a community is a clique/group of nodes within a network that have a higher likelihood of connecting to each other. It could be social networks e.g. data scientists on twitter π or biological systems. Recommended intro: https://t.co/uQfRV06zmh #networks
Day 8: #100DaysOfCode An egocentric network specifically maps the connections of and from the perspective of a single node (an βegoβ). I am exploring how to create and plot an ego network and alters within a particular distance. π’βοΈ