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#data scientist
thedatarogue · 1 year
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All D&D 5E Spells, in one place
Hello, D&D players!
Are you tired of having to go through multiple books, pdf files or third-party websites just to find the one spell you're looking for? Don't want to pay hundreds of dollars to be able to access all the spells in DND Beyond?
Well, I've got just the thing for you.
In this Github repository, I've uploaded a dataset with information on all of the 5E spells (inside the datasets folder). The README file has all the information you need to use it, along with some other stuff.
If you have any problems using these assets, feel free to contact me either through here or Github. I'm thinking of adding pictures to the guide on Github, but it might be a while before I do that.
If the link isn't working, just remove the https://href.li/? part and you should be good.
Happy travels, adventurers.
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catndboots · 6 months
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Things are finally getting serious: Today is the day I will start my journey learning Python from scratch! I really want to improve my coding skills and get more confident. By now, I still often rely on the idea of others, looking at their code and often simply adapt code snippets which fit the present issue to „my solution“ but then couldn‘t replicate a single line without looking at it. I am very excited to change that now, starting to get a deeper understanding and hopefully earn more confidence as a future data scientist!
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d0nutzgg · 9 months
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Tonight I am hunting down venomous and nonvenomous snake pictures that are under the creative commons of specific breeds in order to create one of the most advanced, in depth datasets of different venomous and nonvenomous snakes as well as a test set that will include snakes from both sides of all species. I love snakes a lot and really, all reptiles. It is definitely tedious work, as I have to make sure each picture is cleared before I can use it (ethically), but I am making a lot of progress! I have species such as the King Cobra, Inland Taipan, and Eyelash Pit Viper among just a few! Wikimedia Commons has been a huge help!
I'm super excited.
Hope your nights are going good. I am still not feeling good but jamming + virtual snake hunting is keeping me busy!
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adamsvanrhijn · 5 months
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reblogs appreciated :-)
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theverynearfuture · 1 year
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Not the Droid we were looking for.
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kochivamarketing · 1 month
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Why Study Data Science?
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Data science is an exciting and rewarding field that offers numerous compelling reasons to pursue it as a career path. Here are five key reasons why you should consider studying data science:
High Demand and Lucrative Salaries: With companies across industries recognizing the value of data-driven decision-making, the demand for skilled data scientists is skyrocketing, leading to abundant job opportunities and attractive compensation packages.
Work on Cutting-Edge Technologies: Data science lies at the intersection of emerging technologies like AI, machine learning, big data, and cloud computing, allowing you to work with cutting-edge tools and drive innovation.
Solve Complex Problems and Make an Impact: As a data scientist, you'll tackle real-world challenges across diverse domains, using data to develop solutions that can improve lives, drive social change, and shape the future.
Develop Highly Transferable Skills: Data science requires a unique combination of technical and analytical skills, such as programming, statistics, machine learning, and data visualization, which are highly transferable across industries and job roles.
Join a Vibrant Community: The data science community is diverse, dynamic, and collaborative, offering opportunities for continuous learning, networking, and professional growth through conferences, hackathons, and engagement with like-minded individuals.
With its high demand, potential for innovation, and the ability to make a meaningful impact, data science offers a rewarding and future-proof career path for those driven by intellectual curiosity and a passion for solving complex problems.
If you're in Delhi and looking to kickstart your data science journey, there are several excellent courses to consider, check out - Top 6 Best Data Science Courses in Delhi – The Complete Information
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datascienceunicorn · 1 year
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dcoder0604 · 6 months
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Day 0
Hello guys welcome to my blog. this blog is based on coding life
In this blog, I can share updates on daily codes and data-related work, What I do, and what I don't do on a daily basis
So it will be starting on the 1st of November because my exams are near
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learnandbuild · 1 month
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Summer Internship Program 2024
For More Details Visit Our Website - internship.learnandbuild.in
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jeffinstitute · 1 month
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veryartisangentlemen · 4 months
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Crack the Code: Unraveling the Data Science Course in Vadodara
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Explore the transformative world of data science with eCare Upskill's Data Science Course in Vadodara. Master the art of extracting insights from data, enhancing your career prospects. Our comprehensive program covers key concepts, tools, and real-world applications. Elevate your skills with us and stay ahead in the dynamic field of data science. Call eCare to upskill Now for a FREE demo session at +91 7777919227.
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amayaarora · 4 months
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Embark on a transformative journey into the world of data science with our comprehensive course in Varanasi. Our program, designed for beginners and those seeking to enhance their skills, offers hands-on learning in data analysis, machine learning, and statistics. Taught by industry experts, the course covers practical applications of data science in various domains. With small class sizes, state-of-the-art labs, and flexible payment options, our institute in Varanasi provides an immersive and accessible learning experience. Elevate your career with the power of data – enroll in our Data Science course in Varanasi today!
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catndboots · 7 months
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Step by step. New semester, new chances. Trying to keep up pursuing my goals during that time, finding new hobbies and building healthy routines, although there will be much to do for my data science studies.
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lead-refining · 5 months
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Lead refining using the Harris method.
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vizthedatum · 5 months
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I'm gearing up for Advent of Code 2023 (while trying to be realistic about time constraints with self-care, work, and relationships)!
Who wants to do it with me? I'll mostly be coding in R (in base, tidyverse, and other random paradigms/package bundles), Python, Excel, and (maybe) Rust.
Let's do this work-life-programming balance. (I am a very rusty programmer since I mostly do statistical work - I have the aptitude for it but am very inefficient with optimized solutions.) I'll post my solutions here: https://github.com/pritikadasgupta/adventofcode
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d0nutzgg · 1 year
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Speechy Research Devlog: Some New Tools & New Discoveries
Hey everyone, so it is about 8:30pm and I am sure that by the time I write this it will be nearly 9 but I wanted to update everyone who is following my Speechy research on here. I programmed 2 new programs today, a Prosodic Pitch Analyzer (PPA), and an RMS Energy Analyzer using my handy-dandy new favorite library librosa.
Prosodic Pitch Analyzer
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The PPA calculates the fundamental frequency (F0) or pitch of an audio signal and visualizes it using a line plot. This is a useful tool for analyzing prosodic features of speech such as intonation, stress, and emphasis.
The code takes an audio file as input, processes it using the librosa library to extract the fundamental frequency / pitch, and then plots the pitch contour using matplotlib.
The output plot shows the pitch contour of the audio signal over time, with changes in pitch represented by changes in the vertical position of the line. The plot can be used to identify patterns in the pitch contour, such as rising or falling intonation, and to compare the pitch contour of different audio signals. The prosodic pitch analyzer can be used to detect changes in pitch, which can be indicative of a neurological speech disorder. For example, a person with ataxic dysarthria, which is caused by damage to the cerebellum, may have difficulty controlling the pitch and loudness of their voice, resulting in variations in pitch that are not typical of normal speech. By analyzing changes in pitch using a tool like the prosodic pitch analyzer, it is possible to identify patterns that are indicative of certain neurological disorders. This information can be used by clinicians to diagnose and treat speech disorders, and to monitor progress in speech therapy.
RMS Energy Analyzer
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The program that calculates the energy of a person's speech processes an audio file and calculates the energy of the signal at each time frame. This can be useful for analyzing changes in a person's speech over time, as well as for detecting changes in the intensity or loudness of the speech.
The program uses the librosa library to load and process the audio file, and then calculates the energy of each frame using the root-mean-square (RMS) energy of the signal. The energy values are then plotted over time using the matplotlib library, allowing you to visualize changes in the energy of the speech.
By analyzing changes in energy over time, you can gain insight into how the speech patterns of people with these disorders may differ from those without.
Analysis with PPA
The research that I've been focused on today primarily looked at the speech recording of myself, the mid-stage HD patient with chorea, the late-stage HD patient (EOL), and a young girl with aphasia.
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The patient with aphasia had slurred speech and varied rising and falling much like an AD patient. Earlier I saw her ROS and was surprised at the differences between my rate of speech and hers (aphasia v AD)
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My rate of speech
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The girl with aphasia's rate of speech
So I decided to compare our speech pitches as well and this is what ours looked like side-by-side.
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Hers is on the left, mine on the right.
Her pitch seemed to start off higher (unstable though) like mine, but mine fell during my recording and wobbled for a while. She had some drastic pitch differences but mine had around 16 peaks, where hers had around 18-19. Her latter peaks weren't as high frequency as mine, as my frequency peaks ended up mostly very high in the 1600hz or around 1000hz. There is quite a bit of instability in both our pitches though.
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Her energy levels in the 15 seconds of speech started off at high-mid energy, then dropped around 1 second in until almost 3 seconds, shot back up and varied in high, high-mid energy, then had several "dips, and higher moments of energy. At the end around 13 seconds she got a huge boost of "gusto" (well.. energy). She had around 7 breaths (noted by the dips / flatlines)
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This was mine. It seems like as the 15 seconds went on I started to run out of steam. I wasn't able to keep my energy higher. Mine had around 11 breaths so I was running out of breath eg having a breathier voice more than she was.
Research Conclusion for Today
Although we have quite a bit in common with our speech energy and pitches, our rate of speaking isn't. She used more syllables at a constant rate which made it pretty obvious she had a lot of slurring / overshooting, mine was a lot less syllables and rate of speech was quite slow and varied more than hers. This illustrates my cognitive difficulties and use of placeholder words along with slight slurring.
As far as pitch, seems that we had similar issues with pitch throughout the 15 second clips, mine spiked in the latter when I was getting "wore out" and hers spiked earlier when she had more energy.
Our energy levels differ because although she had moments of energy, I tuckered out pretty quickly.
I hope this helps shed some insight into both aphasia patients and ataxic dysarthria / HD patients speech / some cognitive differences.
Will update again tomorrow when I am done with another day of programming and research!
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