𝗦𝘁𝗮𝗿𝘁 𝗮 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗼𝗿 𝗧𝗲𝗰𝗵 (𝗙𝗿𝗲𝗲 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗮𝘁𝗵)😍
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❤1
Useful Telegram Channels to boost your career 😄👇
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Free Courses with Certificate
Web Development
Data Science & Machine Learning
Programming books
Python Free Courses
Data Analytics
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Excel
ChatGPT Hacks
SQL
Tableau & Power BI
Coding Projects
Data Science Projects
Jobs & Internship Opportunities
Coding Interviews
Udemy Free Courses with Certificate
Cryptocurrency & Bitcoin
Python Projects
Data Analyst Interview
Data Analyst Jobs
Python Interview
ChatGPT Hacks
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❤5
Forwarded from Python Projects & Resources
𝗖𝗜𝗦𝗖𝗢 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
- Data Analytics
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- Cybersecurity
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❤1
Artificial Intelligence (AI) is the simulation of human intelligence in machines that are designed to think, learn, and make decisions. From virtual assistants to self-driving cars, AI is transforming how we interact with technology.
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
❤5
7 ChatGPT Prompts To Transform Your Life In Next 30 Days:
[Save for later]
[Save for later]
❤1
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 ,𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 ,𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 & 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗚𝘂𝗶𝗱𝗲😍
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Forwarded from Artificial Intelligence
𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗔𝗽𝗽𝗿𝗼𝘃𝗲𝗱 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 😍
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Whether you’re interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, there’s something here for everyone.
✅ 100% Free Courses
✅ Govt. Incentives on Completion
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✅ Certificates to Showcase on LinkedIn & Resume
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𝐋𝐢𝐧𝐤 👇:-
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👨🎓The Best Courses for AI from Universities with YouTube Playlists
Stanford University Courses
•CS221 - Artificial Intelligence: Principles and Techniques
•CS224U: Natural Language Understanding
•CS224n - Natural Language Processing with Deep Learning
•CS229 - Machine Learning
•CS230 - Deep Learning
•CS231n - Convolutional Neural Networks for Visual Recognition
•CS234 - Reinforcement Learning
•CS330 - Deep Multi-task and Meta-Learning
•CS25 - Transformers United
Carnegie Mellon University Courses
•CS 10-708: Probabilistic Graphical Models
•CS/LTI 11-711: Advanced NLP
•CS/LTI 11-737: Multilingual NLP
•CS/LTI 11-747: Neural Networks for NLP
•CS/LTI 11-785: Introduction to Deep Learning
•CS/LTI 11-785: Neural Networks
Massachusetts Institute of Technology Courses
•Introduction to Algorithms
•Introduction to Deep Learning
•6.S094 - Deep Learning
DeepMind x UCL
•COMP M050 - Introduction to Reinforcement Learning
•Deep Learning Series
Stanford University Courses
•CS221 - Artificial Intelligence: Principles and Techniques
•CS224U: Natural Language Understanding
•CS224n - Natural Language Processing with Deep Learning
•CS229 - Machine Learning
•CS230 - Deep Learning
•CS231n - Convolutional Neural Networks for Visual Recognition
•CS234 - Reinforcement Learning
•CS330 - Deep Multi-task and Meta-Learning
•CS25 - Transformers United
Carnegie Mellon University Courses
•CS 10-708: Probabilistic Graphical Models
•CS/LTI 11-711: Advanced NLP
•CS/LTI 11-737: Multilingual NLP
•CS/LTI 11-747: Neural Networks for NLP
•CS/LTI 11-785: Introduction to Deep Learning
•CS/LTI 11-785: Neural Networks
Massachusetts Institute of Technology Courses
•Introduction to Algorithms
•Introduction to Deep Learning
•6.S094 - Deep Learning
DeepMind x UCL
•COMP M050 - Introduction to Reinforcement Learning
•Deep Learning Series
❤3
Forwarded from Artificial Intelligence
𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 & 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗢𝗳𝗳𝗲𝗿𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
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Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
Enroll for FREE & Get Certified 🎓
❤2
Artificial Intelligence with Python - 2022.pdf
9.5 MB
Artificial Intelligence with Python
Teik Toe Teoh, 2022
Teik Toe Teoh, 2022
❤2
Forwarded from Artificial Intelligence
𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬!🚀💻
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𝗙𝗿𝗲𝗲 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗼𝘂𝗿𝘀𝗲 𝗳𝗼𝗿 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿𝘀😍
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This 100% FREE course is designed just for beginners — whether you’re a student, fresher, or career switcher✅️
Want to explore AI & Machine Learning but don’t know where to start — or don’t want to spend ₹₹₹ on it?👨💻
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𝐋𝐢𝐧𝐤👇:-
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This 100% FREE course is designed just for beginners — whether you’re a student, fresher, or career switcher✅️
❤2