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🙈 8 free NVIDIA artificial intelligence courses

🇸🇾 The NVIDIA site has released a series of artificial intelligence courses that are extremely practical and free for students who want to learn more about this field and are still at the beginning of the journey. 💯

1️⃣ Generative AI Explained course
📝 Definition of productive intelligence and how it works
🗂 Link: LINK

2️⃣ Building A Brain course
📝 How neural networks use data for learning.
🗂 Link: LINK

3️⃣ Augment your LLM Using RAG course
📝 Familiarity with RAG recovery process.
🗂 Link: LINK

4️⃣ Intro to AI in the Data Center course
📝 What is artificial intelligence and its applications.
🗂 Link: LINK

5️⃣ Accelerate Data Science Workflows course
📝 Understand the benefits of integrated workflow between CPUs and GPUs for data science tasks.
*🗂 *Link: LINK

6️⃣ Recommender Systems course
📝 Strategies used to excel in a data science competition focused on building a recommendation system.
🗂 Link: LINK

7️⃣ Introduction to Networking course
📝 What is the network and why it is needed.
🗂 Link: LINK

8️⃣ Large-Scale Image Classification course
An introduction to large-scale image classification.
🗂 Link: LINK

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♾ 32 essential datasets for data science projects

🔴 The Data Science Dojo website has created a collection of 32 datasets with different levels of difficulty to practice and improve your skills as a data scientist.

✅ This collection includes a diverse range of topics that are classified according to the level of difficulty so that it is suitable for everyone and challenges your theoretical knowledge and practical experience in different parts of data science, such as data cleaning, data visualization, machine learning, etc.

*🟢* Basic Level

┌ 🏷 Datasets
├ 🟡 Abalone ├ 🟡 User Knowledge Modeling ├ 🟡 Real Estate Valuation ├ 🟡 Wireless Indoor Localization ├ 🟡Car Evaluation ├ 🟡 Fertility └ 🟡 Qualitative Bankruptcy 🟡 Intermediate Level

┌ 🏷 Datasets
├ 🔸 Auto MPG ├ 🔸 Heart Disease ├ 🔸 Daily Demand Forecasting Orders ├ 🔸 Blood Transfusion Service Center ├ 🔸 Beijing PM2.5 ├ 🔸 Echocardiogram ├ 🔸 Concrete Compressive Strength ├ 🔸 Liver Disorders ├ 🔸Dow Jones Index ├ 🔸Energy Efficiency ├ 🔸 Glass Identification ├ 🔸 Hepatitis ├ 🔸 Wholesale Customers └ 🔸Travel Reviews ├ 🔸 Istanbul Stock Exchange ├ 🔸 Bike Sharing ├ 🔸 Occupancy Detection ├ 🔸 Census Income └ 🔸 Coronavirus 🔴 Advanced Level

┌ 🏷 Generative AI for Beginners
├ 🔸 Autism Screening Adult ├ 🔸 Default of Credit Card Clients ├ 🔸 Banknote Authentication ├ 🔸 Individual Household Electric Power ├ 🔸 Online News Popularity └ 🔸** Amazon Product Reviews

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190+ Python Interview Questions and Answers (2024)

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Support Vector Machines in OpenCV

Article: https://machinelearningmastery.com/support-vector-machines-in-opencv/

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Artificial Intelligence && Deep Learning
Channel for who have a passion for -

• Artificial Intelligence
• Machine Learning
• Deep Learning
• Data Science
• Computer vision
• Image Processing
• Research Papers

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import PyPDF2 import pyttsx3 \# Read the pdf by specifying the path in your computer pdfReader = PyPDF2.PdfFileReader(open('clcoding.pdf', 'rb')) \# Get the handle to speaker speaker = pyttsx3.init() \# split the pages and read one by one for page\_num in range(pdfReader.numPages): text = pdfReader.getPage(page\_num).extractText() speaker.say(text) speaker.runAndWait() \# stop the speaker after completion speaker.stop() \# save the audiobook at specified path engine.save\_to\_file(text, 'E:\audio.mp3') engine.runAndWait()

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