53.7K
EDAnaconda is a Python distribution that supports separate environments. Library version conflicts are a bug problem with Python that Anaconda helps you avoid.
@edhonour
#Matplotlib Latest Features
Schauen Sie sich Reels-Videos über Matplotlib Latest Features von Menschen aus aller Welt an.
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PYMatplotlib in 1 Minute – Simple Python Plots
@pythonclcoding
2.9M
ISTry THIS on ChatGPT!
Level up your prompting skills with RTCROS prompts:
Role
Task
Context
Reasoning
Output format
Stopping condition
#ai #chatgpt #aitools #artificialintelligence
@ishansharma7390
6.2K
_N.
دو کاربرد مهم دیگه اش هم در امنیت سایبری و هک هست و همچنین در بیوانفورماتیک
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🧠 دوره آموزشی پایتون از صفر (دوره دهم)
🧠 Python for beginners
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🔰 برگزار کننده :
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نوروسافاری – موسسه آینده مغز
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🔰 شروع کلاسها: ۶ خرداد ۱۴۰۲
آخرین مهلت ثبت نام: ۵ خرداد
🔰ظرفیت کلاسها: ۱۲ نفر آنلاین بر اساس اولویت ثبت نام
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🔰تعداد ساعات تدریس: ۱۶ ساعت در ۴ هفته
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🔰روزهای برگزاری: شنبه ها و دوشنبه ها ۷ تا ۹ عصر
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📃با گواهی معتبر انگلیسی موثر در اپلای
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✅ سر فصل های دوره:
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🔹آشنایی با زبان برنامه نویسی پایتون
🔹اصول اولیه برنامه نویسی پایتون
🔹طریقه نصب و کار با پایتون
🔹ذخیره سازی، تغییر و مدیریت اطلاعات در پایتون
🔹نحوه رفع خطاهای احتمالی
🔹کار با مجموعه ها در پایتون
🔹توابع در پایتون
🔹تعریف و استفاده از ماژول ها
🔹پارامتر ها و آرگومان های تابع و انواع آنها
تعریف و نحوه استفاده از شرطی ها و بازگشت
🔹تعریف عملگرها و نحوه استفاده از آنها
🔹پکیج Matplotlib
🔹کار با دیکشنری ها
🔹شرط ها و حلقه ها (Loops and Conditions)
🔹ساخت پکیج در پایتون
🔹یادگیری مبانی فرمول نویسی
🔹آشنایی با پکیج های پایتون
🔹پکیج پانداس و نامپای و …..
لینک برای اطلاعات بیشتر:
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🌐 http://www.neurosafari.com/دوره-آموزشی-پایتون-از-صفر-دوره-دهم
برای ثبت نام با ایمیل زیر در ارتباط باشید:
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📧 info@neurosafari.com
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یا به اکانت موسسه آینده مغز پیام دایرکت بدهید:
@_neurosafari_
⚠️ برای دیگران هم ارسال کنید
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کانال تلگرام نوروسافاری:
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🆔 t.me/neurosafari1
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#پایتون #برنامه_نویسی #برنامه_نویسی_پایتون #پایتون_نویسی #پایتون_مقدماتی #پایتون_فارسی #پایتون_آنلاین #آموزش #آموزش_پایتون #پکیج #کد #کدزدن #کد_زدن #کدنویسی #برنامه #کدنویس #کدنویسی_آسان #نوروساینس #نوروسافاری #آینده_مغز
@_neurosafari_
16.0K
MARun PyTorch models and collaborate with Git—all in MATLAB Online
✔️ Bring PyTorch models into your browser
✔️ Use Git for version control
✔️ Work end-to-end on deep learning projects
🔗 Link in bio for the guide
@matlab
2.5K
TEEasily render charts using this python trick!
@tech_with_tim
1.2K
DA🔢Day 148– Data Science Journey(Machine Learning)
📊Topic : PCA(Principal Composition Analysis)
Today ,I explored on the topic Unsupervised Machine Learning Algorithm ,understand theory and Implementation on Jupiter Notebook
**PCA (Principal Component Analysis) :- is a dimensionality reduction technique used in data analysis and machine learning. It helps you to reduce the number of features in a dataset while keeping the most important information.
Note: It prioritizes the directions where the data varies the most because more variation = more useful information.
**How to find the vector >
->Eigen Values and Eigen Vectors
1. Covariance Matrix Between features
A=Cov[f1,f2]
2. Eigen values and eigen vector find out using covariance matrix
A.v=lambda*v
lambda->Eigen vector
v->Eigen value
Implentation Of PCA On Jupiter Notebook
->import libraries ,numpy , matplotlib
->from sklearn.decomposition import PCA
->from sklearn import datasets ,use load_iris()
->4Dimension in dataset ,and convert 4D to 3D
->separate independent(X) and dependent(Y) variables
->further divide train_test_split(X_train,X_test,y_train,y_test)
->then find out shape of train_test_split
->PCA(n_components=3) ,which means no of components are 3
->pca.fit_transform(X_train),in training converts 4D to 3D form
->pca.transform(X_test),in testing phase it also show 4D to 3D form
->pca.components_ - it shows total number of components
->pca.explained_variance_ratio_ , which shows summation all of these 3D form and find out large variance
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GITHUB ---https://github.com/santoshkr123/Data-science-/blob/main/Day148pca-principlecomponentanalysis.ipynb
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#datasciencewithsantosh
@datasciencewithsantosh
1.6M
ME↓ read caption (+save for later!)
𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟭: 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 🚀
Engage in cutting-edge technology by crafting an AI-powered virtual assistant. Build a conversational interface using natural language processing (NLP) libraries like Dialogflow or Rasa.
→ 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼?
Explore NLP concepts, design conversation flows, and develop the assistant using the chosen library.
𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟮: 𝗗𝗮𝘁𝗮 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝘄𝗶𝘁𝗵 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 📊
Build a data dashboard that displays insights and trends from a real-world dataset. Utilize visualization libraries like D3.js, Plotly, or Matplotlib.
→ 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼?
Choose a dataset that interests you, clean and preprocess it, then delve into visualization techniques to highlight key patterns.
𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟯: 𝗘-𝗖𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗪𝗲𝗯𝘀𝗶𝘁𝗲 🛒
Create a fully functional e-commerce website that demonstrates your proficiency in full-stack development.
→ 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼?
Plan the structure of your website, design wireframes, and decide on the tech stack. Break down the features and implement them step by step.
𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟰: 𝗔𝗣𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 🌐
Develop an application that utilizes external APIs to provide valuable services to users. This could be a weather app, language translator, currency converter, or a news aggregator.
→ 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼?
Identify APIs that align with your chosen application concept and study their documentation. Build the application with a user-friendly interface to access and display data from these APIs.
𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝟱: 𝗛𝗼𝗺𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗦𝘆𝘀𝘁𝗲𝗺 𝘄𝗶𝘁𝗵 𝗜𝗼𝗧 🤖
Develop a central hub that controls smart devices like lights, thermostats, and security cameras.
→ 𝗪𝗵𝗮𝘁 𝗰𝗮𝗻 𝘆𝗼𝘂 𝗱𝗼?
Research IoT protocols, acquire compatible devices, and program the hub to manage the devices through a user-friendly interface.
FOLLOW me @meakcodes for more!
◦ ◦ ◦ ◦ ◦ ◦ ◦
#programming #programmers #developers #webdeveloper #softwaredeveloper #devlife #coding #setup #tips #studentTips
@meakcodes
328
THBREAKING 🚨: An open source Gemini CLI is now integrated into an open source Zed code editor!
Documented 🗞️
https://www.testingcatalog.com/google-introduces-gemini-cli-integration-in-zed-editor/
@theaiempire_
146.3K
SH💡 با پایتون هر کاری ممکنه!
از ساخت بازیهای جذاب 🎮 تا تحلیل دادههای پیچیده 📊، پایتون راهحلی برای همه چیز داره! 🚀
کدوم ترکیبش برات جذابتره؟ 🤔👇
#پایتون #برنامهنویسی #توسعه_وب #یادگیری_ماشین #تحلیل_داده #کدنویسی #شریفی_باش
@sharifibash
86.3K
TIPOV: you’re bored so you use AI to code you a machine learning model that will predict the upcoming F1 Spain GP! How do you think it did?! Here is the prompt I used 👇
Build a Python machine learning project that predicts the winner of the 2025 Spanish Grand Prix using historical Formula 1 data.
Use the Ergast API to pull past race data (results, qualifying, drivers, constructors), with a focus on the Circuit de Barcelona-Catalunya.
Include steps to:
Download and process the race, qualifying, and constructor standings data from 2015 to 2024.
Engineer features like qualifying position, team performance, previous wins at this circuit, and current season form.
Train a classification model (Random Forest or XGBoost) to predict the winning driver for a given race.
Output the top 3 predicted drivers for the 2025 Spanish GP given mock qualifying positions and current standings.
Use pandas for data processing, scikit-learn or XGBoost for modeling, and matplotlib for any charts.
Make sure the code is modular with functions for:
load_data()
feature_engineering()
train_model()
predict_2025_spanish_gp()
#tech #technology #stem #dev
@tiffintech
1.0M
KAThe latest humanoid robots are starting to feel like Black Mirror.
This is the Figure 03.
Figure 03 is 5’ 8”, 134 pounds, and engineered to think and act like a human.
This version specifically was designed for in-home use.
So it can do laundry, wash dishes, serve drinks, deliver packages.
It even charges wirelessly through its feet.
It kinda just stands creepily on that charging pad until it wakes up and starts doing more chores.
12,000 people are going to have one of these in their homes within the next 12 months.
100,000 people will get one in the next 4 years.
But as cool as it looks, the most interesting part about this is not actually the robot itself.
The most interesting part is Figure’s AI training system…Helix.
Every Figure robot has a bunch of cameras and sensors in its face and both of its hands.
So as it does more tasks, it’s watching and learning from the world around it.
But the learning isn’t just to help the one robot doing it.
The skills are feeding back to the global AI system, which automatically upskills the entire fleet.
And you can see where this is going.
Just like ChatGPT gets better as more people use it…the more robots that do stuff in the world, the faster they will all get smarter.
What you’re watching is the very early innings of another massive tech supercycle.
And Black Mirror or not, we are officially entering the beginning of the Robot Age.
Follow @kallaway for more videos like this!
#ai #artificialintelligence #tech #technology #robots #robotics #humanoid #figure #newtech #future
@kallaway
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