๐ Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
โค4
Use Chat GPT to prepare for your next Interview
This could be the most helpful thing for people aspiring for new jobs.
A few prompts that can help you here are:
๐กPrompt 1: Here is a Job description of a job I am looking to apply for. Can you tell me what skills and questions should I prepare for? {Paste JD}
๐กPrompt 2: Here is my resume. Can you tell me what optimization I can do to make it more likely to get selected for this interview? {Paste Resume in text}
๐กPrompt 3: Act as an Interviewer for the role of a {product manager} at {Company}. Ask me 5 questions one by one, wait for my response, and then tell me how I did. You should give feedback in the following format: What was good, where are the gaps, and how to address the gaps?
๐กPrompt 4: I am interviewing for this job given in the JD. Can you help me understand the company, its role, its products, main competitors, and challenges for the company?
๐กPrompt 5: What are the few questions I should ask at the end of the interview which can help me learn about the culture of the company?
Free book to master ChatGPT: https://t.me/InterviewBooks/166
ENJOY LEARNING ๐๐
This could be the most helpful thing for people aspiring for new jobs.
A few prompts that can help you here are:
๐กPrompt 1: Here is a Job description of a job I am looking to apply for. Can you tell me what skills and questions should I prepare for? {Paste JD}
๐กPrompt 2: Here is my resume. Can you tell me what optimization I can do to make it more likely to get selected for this interview? {Paste Resume in text}
๐กPrompt 3: Act as an Interviewer for the role of a {product manager} at {Company}. Ask me 5 questions one by one, wait for my response, and then tell me how I did. You should give feedback in the following format: What was good, where are the gaps, and how to address the gaps?
๐กPrompt 4: I am interviewing for this job given in the JD. Can you help me understand the company, its role, its products, main competitors, and challenges for the company?
๐กPrompt 5: What are the few questions I should ask at the end of the interview which can help me learn about the culture of the company?
Free book to master ChatGPT: https://t.me/InterviewBooks/166
ENJOY LEARNING ๐๐
โค3๐ฉ1
Which AI is better โ with a wrapper or without?
I liked a slide from the recent presentation Sequoia Capital AI Ascent 2025.
Big vendors after the launch of ChatGPT insisted that niche and industrial startups consuming AGI intelligence are unpromising.
They disdainfully called them AI wrappers, believing that they have no protection against competitors.
A couple of years later, we observe record growth precisely in such companies as Cursor ($300 million ARR), Loveable, Windsurf (bought by OpenAI for $3 billion), and thousands of new industrial startups โ in finance, insurance, e-commerce, legal, accounting, healthcare, and other sectors.
Meanwhile, AI tokens are becoming the fastest depreciating technology and currency in history.
According to Sam Altman himself, over time the cost of AI will equal the cost of energy.
Giants have started giving access to their most powerful AI models to seize leadership in the new technological era.
I have already written about a unique market moment: when, being an expert in any subject area, you combine your knowledge with the growing capabilities of AI โ and get a tool that solves real human problems for which clients are ready to pay immediately.
Now these very AI wrappers have turned into serious businesses.
The obvious challenge for entrepreneurs is that AI skills and specialists are increasing in value much faster than other segments of the IT market.
Startups and mature companies with subject matter experts already face difficulties attracting strong AI engineers, but at the same time, according to the results of the first internal hackathons, I see a rapid increase in the number of those who caught the trend and felt in AI a breath of fresh air in the enterprise world.
In the coming years, young founders and enthusiasts who live by technology, see trends ahead, and tirelessly experiment by creating new products will win rapidly.
Time to act!
I liked a slide from the recent presentation Sequoia Capital AI Ascent 2025.
Big vendors after the launch of ChatGPT insisted that niche and industrial startups consuming AGI intelligence are unpromising.
They disdainfully called them AI wrappers, believing that they have no protection against competitors.
A couple of years later, we observe record growth precisely in such companies as Cursor ($300 million ARR), Loveable, Windsurf (bought by OpenAI for $3 billion), and thousands of new industrial startups โ in finance, insurance, e-commerce, legal, accounting, healthcare, and other sectors.
Meanwhile, AI tokens are becoming the fastest depreciating technology and currency in history.
According to Sam Altman himself, over time the cost of AI will equal the cost of energy.
Giants have started giving access to their most powerful AI models to seize leadership in the new technological era.
I have already written about a unique market moment: when, being an expert in any subject area, you combine your knowledge with the growing capabilities of AI โ and get a tool that solves real human problems for which clients are ready to pay immediately.
Now these very AI wrappers have turned into serious businesses.
The obvious challenge for entrepreneurs is that AI skills and specialists are increasing in value much faster than other segments of the IT market.
Startups and mature companies with subject matter experts already face difficulties attracting strong AI engineers, but at the same time, according to the results of the first internal hackathons, I see a rapid increase in the number of those who caught the trend and felt in AI a breath of fresh air in the enterprise world.
In the coming years, young founders and enthusiasts who live by technology, see trends ahead, and tirelessly experiment by creating new products will win rapidly.
Time to act!
โค4๐1
๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐๐
๐๐ฝ๐ฝ๐น๐ ๐๐ถ๐ป๐ธ๐:-๐
S&P Global :- https://pdlink.in/3ZddwVz
IBM :- https://pdlink.in/4kDmMKE
TVS Credit :- https://pdlink.in/4mI0JVc
Sutherland :- https://pdlink.in/4mGYBgg
Other Jobs :- https://pdlink.in/44qEIDu
Apply before the link expires ๐ซ
๐๐ฝ๐ฝ๐น๐ ๐๐ถ๐ป๐ธ๐:-๐
S&P Global :- https://pdlink.in/3ZddwVz
IBM :- https://pdlink.in/4kDmMKE
TVS Credit :- https://pdlink.in/4mI0JVc
Sutherland :- https://pdlink.in/4mGYBgg
Other Jobs :- https://pdlink.in/44qEIDu
Apply before the link expires ๐ซ
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 hasnโt 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 hasnโt been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
โค2
Forwarded from Artificial Intelligence
๐ฐ ๐๐ฟ๐ฒ๐ฒ ๐ฃ๐๐๐ต๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐๐ผ๐ผ๐๐ ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ฒ๐๐๐บ๐ฒ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Want to Boost Your Resume with In-Demand Python Skills?๐จโ๐ป
In todayโs tech-driven world, Python is one of the most in-demand programming languages across data science, software development, and machine learning๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Hnx3wh
Enjoy Learning โ ๏ธ
Want to Boost Your Resume with In-Demand Python Skills?๐จโ๐ป
In todayโs tech-driven world, Python is one of the most in-demand programming languages across data science, software development, and machine learning๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Hnx3wh
Enjoy Learning โ ๏ธ
โค1
ChatGPT can help you land your dream job twice as fast. Here are 8 powerful ChatGPT prompts will 10X your interview chances.
Free book to master ChatGPT: https://t.me/InterviewBooks/166
1. Customizing Your Resume ChatGPT prompt: "Can you make changes to my resume to fit the [Job Title] role at [Company]? Here's the job description: [Paste Job Description], and resume: [Paste Resume]."
2. Creating a Professional Summary ChatGPT prompt: "Using my resume, can you create a professional summary for me aligned to this [Job Title]." [Paste Resume]
3. Understanding Job Descriptions ChatGPT prompt: "What are the main responsibilities for this job? Please list the top three responsibilities required for [Job Title]." [Paste Job Description]
4. Improving Your Resume Bullets ChatGPT prompt: "Please rewrite this bullet point from my resume using clear and impactful language while highlighting my accomplishments. [Paste Resume]"
5. Writing a LinkedIn Summary ChatGPT prompt: "Can you write a summary for my LinkedIn profile using my resume [Paste Resume]?"
6. Job Applications with ChatGPT ChatGPT prompt: "Can you identify my [Skills] experience from my resume [Paste Resume]? Please describe my specific [Skills] experience in conversational, clear language as if you were me."
7. Crafting Your Cover Letter ChatGPT prompt: "Can you write a personalized cover letter for the [Job Title] position at [Company]? Here's the job description: [Paste Job Description], and my current resume: [Paste Resume]."
8. Preparing for Interviews ChatGPT prompt: "What skills and experiences should I emphasize during an interview for the [Job Title] role in [Specific Industry]?"
ENJOY LEARNING ๐๐
Free book to master ChatGPT: https://t.me/InterviewBooks/166
1. Customizing Your Resume ChatGPT prompt: "Can you make changes to my resume to fit the [Job Title] role at [Company]? Here's the job description: [Paste Job Description], and resume: [Paste Resume]."
2. Creating a Professional Summary ChatGPT prompt: "Using my resume, can you create a professional summary for me aligned to this [Job Title]." [Paste Resume]
3. Understanding Job Descriptions ChatGPT prompt: "What are the main responsibilities for this job? Please list the top three responsibilities required for [Job Title]." [Paste Job Description]
4. Improving Your Resume Bullets ChatGPT prompt: "Please rewrite this bullet point from my resume using clear and impactful language while highlighting my accomplishments. [Paste Resume]"
5. Writing a LinkedIn Summary ChatGPT prompt: "Can you write a summary for my LinkedIn profile using my resume [Paste Resume]?"
6. Job Applications with ChatGPT ChatGPT prompt: "Can you identify my [Skills] experience from my resume [Paste Resume]? Please describe my specific [Skills] experience in conversational, clear language as if you were me."
7. Crafting Your Cover Letter ChatGPT prompt: "Can you write a personalized cover letter for the [Job Title] position at [Company]? Here's the job description: [Paste Job Description], and my current resume: [Paste Resume]."
8. Preparing for Interviews ChatGPT prompt: "What skills and experiences should I emphasize during an interview for the [Job Title] role in [Specific Industry]?"
ENJOY LEARNING ๐๐
โค5
Forwarded from Artificial Intelligence
๐ ๐ฎ๐๐๐ฒ๐ฟ ๐ฒ ๐๐ป-๐๐ฒ๐บ๐ฎ๐ป๐ฑ ๐ฆ๐ธ๐ถ๐น๐น๐ ๐ณ๐ผ๐ฟ ๐๐ฅ๐๐!๐
Want to boost your career with highly sought-after tech skills? These 6 YouTube channels will help you learn from scratch!๐จโ๐ป
No need for expensive coursesโstart learning for FREE today!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ddxd7P
Donโt miss this opportunityโstart learning today and take your skills to the next level!โ ๏ธ
Want to boost your career with highly sought-after tech skills? These 6 YouTube channels will help you learn from scratch!๐จโ๐ป
No need for expensive coursesโstart learning for FREE today!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3Ddxd7P
Donโt miss this opportunityโstart learning today and take your skills to the next level!โ ๏ธ
โค1
Forwarded from Python Projects & Resources
๐ง๐ต๐ฒ ๐๐ฒ๐๐ ๐๐ฟ๐ฒ๐ฒ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ต๐ฒ๐ฎ๐ ๐ฆ๐ต๐ฒ๐ฒ๐ ๐ผ๐ป ๐๐ถ๐๐๐๐ฏ ๐๐๐ฒ๐ฟ๐ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ ๐ฆ๐ต๐ผ๐๐น๐ฑ ๐๐ผ๐ผ๐ธ๐บ๐ฎ๐ฟ๐ธ๐
๐ง Master Data Science Faster with This Free GitHub Cheat Sheet๐
Whether youโre starting your data science journey or preparing for job interviews, having the right revision tool can make all the difference๐ฏ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4klQmF3
Must-have resource for students and professionalsโ ๏ธ
๐ง Master Data Science Faster with This Free GitHub Cheat Sheet๐
Whether youโre starting your data science journey or preparing for job interviews, having the right revision tool can make all the difference๐ฏ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4klQmF3
Must-have resource for students and professionalsโ ๏ธ
โค1
This is a class from Harvard University:
"Introduction to Data Science with Python."
It's free. You should be familiar with Python to take this course.
The course is for beginners. It's for those who want to build a fundamental understanding of machine learning and artificial intelligence.
It covers some of these topics:
โข Generalization and overfitting
โข Model building, regularization, and evaluation
โข Linear and logistic regression models
โข k-Nearest Neighbor
โข Scikit-Learn, NumPy, Pandas, and Matplotlib
Link: https://pll.harvard.edu/course/introduction-data-science-python
"Introduction to Data Science with Python."
It's free. You should be familiar with Python to take this course.
The course is for beginners. It's for those who want to build a fundamental understanding of machine learning and artificial intelligence.
It covers some of these topics:
โข Generalization and overfitting
โข Model building, regularization, and evaluation
โข Linear and logistic regression models
โข k-Nearest Neighbor
โข Scikit-Learn, NumPy, Pandas, and Matplotlib
Link: https://pll.harvard.edu/course/introduction-data-science-python
โค2
Forwarded from Python Projects & Resources
๐ฑ ๐ ๐๐๐-๐๐ผ๐น๐น๐ผ๐ ๐ฌ๐ผ๐๐ง๐๐ฏ๐ฒ ๐๐ต๐ฎ๐ป๐ป๐ฒ๐น๐ ๐ณ๐ผ๐ฟ ๐๐๐ฝ๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐๐ถ๐๐๐ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Want to Become a Data Scientist in 2025? Start Here!๐ฏ
If youโre serious about becoming a Data Scientist in 2025, the learning doesnโt have to be expensive โ or boring!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4kfBR5q
Perfect for beginners and aspiring prosโ ๏ธ
Want to Become a Data Scientist in 2025? Start Here!๐ฏ
If youโre serious about becoming a Data Scientist in 2025, the learning doesnโt have to be expensive โ or boring!๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4kfBR5q
Perfect for beginners and aspiring prosโ ๏ธ
๐๐ผ๐ ๐๐ผ ๐๐ฒ๐ ๐ฆ๐๐ฎ๐ฟ๐๐ฒ๐ฑ ๐ถ๐ป ๐๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ถ๐ฎ๐น ๐๐ป๐๐ฒ๐น๐น๐ถ๐ด๐ฒ๐ป๐ฐ๐ฒ ๐๐ถ๐๐ต ๐ญ๐ฒ๐ฟ๐ผ ๐๐
๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ!๐ง โก
AI might sound complex. But guess what?
You donโt need a PhD or 5 years of experience to break into this field.
Hereโs your 6-step beginner roadmap to launch your AI journey the smart way๐
๐น ๐ฆ๐๐ฒ๐ฝ ๐ญ: Learn the Basics of Python (Your AI Superpower)
Python is the language of AI.
โ Learn variables, loops, functions, and data structures
โ Practice with platforms like W3Schools, SoloLearn, or Replit
โ Understand NumPy & Pandas basics (theyโll be your go-to tools)
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฎ: Understand What AI Really Is
Before diving deep, get clarity.
โ What is AI vs ML vs Deep Learning?
โ Learn core concepts like Supervised vs Unsupervised Learning
โ Follow beginner-friendly YouTubers like โStatQuestโ or โCodebasicsโ
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฏ: Build Simple AI Projects (Even as a Beginner)
Start applying your skills with fun mini-projects:
โ Spam Email Classifier
โ House Price Predictor
โ Rock-Paper-Scissors Game using AI
Pro Tip: Use scikit-learn for most of these!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฐ: Get Comfortable with Data (AI Runs on It!)
AI = Algorithms + Data
โ Learn basic data cleaning with Pandas
โ Explore simple datasets from Kaggle or UCI ML Repository
โ Practice EDA (Exploratory Data Analysis) with Matplotlib & Seaborn
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฑ: Take Free AI Courses (No Cost Learning)
You donโt need a fancy bootcamp to start learning.
โ โAI For Everyoneโ by Andrew Ng (Coursera)
โ โMachine Learning with Pythonโ by IBM (edX)
โ Kaggleโs Learn Track: Intro to ML
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฒ: Join AI Communities & Share Your Work
โ Join AI Discord servers, Reddit threads, and LinkedIn groups
โ Post your projects on GitHub
โ Engage in AI hackathons, challenges, and build in public
Your network = Your next opportunity.
๐ฏ ๐ฌ๐ผ๐๐ฟ ๐๐ถ๐ฟ๐๐ ๐๐ ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ = ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฟ๐ ๐ฃ๐ผ๐ถ๐ป๐
Itโs not about knowing everythingโitโs about starting.
Consistency will compound.
Youโll go from โbeginnerโ to โbuilderโ faster than you think.
Free Artificial Intelligence Resources: https://whatsapp.com/channel/0029VaoePz73bbV94yTh6V2E
#ai
AI might sound complex. But guess what?
You donโt need a PhD or 5 years of experience to break into this field.
Hereโs your 6-step beginner roadmap to launch your AI journey the smart way๐
๐น ๐ฆ๐๐ฒ๐ฝ ๐ญ: Learn the Basics of Python (Your AI Superpower)
Python is the language of AI.
โ Learn variables, loops, functions, and data structures
โ Practice with platforms like W3Schools, SoloLearn, or Replit
โ Understand NumPy & Pandas basics (theyโll be your go-to tools)
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฎ: Understand What AI Really Is
Before diving deep, get clarity.
โ What is AI vs ML vs Deep Learning?
โ Learn core concepts like Supervised vs Unsupervised Learning
โ Follow beginner-friendly YouTubers like โStatQuestโ or โCodebasicsโ
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฏ: Build Simple AI Projects (Even as a Beginner)
Start applying your skills with fun mini-projects:
โ Spam Email Classifier
โ House Price Predictor
โ Rock-Paper-Scissors Game using AI
Pro Tip: Use scikit-learn for most of these!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฐ: Get Comfortable with Data (AI Runs on It!)
AI = Algorithms + Data
โ Learn basic data cleaning with Pandas
โ Explore simple datasets from Kaggle or UCI ML Repository
โ Practice EDA (Exploratory Data Analysis) with Matplotlib & Seaborn
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฑ: Take Free AI Courses (No Cost Learning)
You donโt need a fancy bootcamp to start learning.
โ โAI For Everyoneโ by Andrew Ng (Coursera)
โ โMachine Learning with Pythonโ by IBM (edX)
โ Kaggleโs Learn Track: Intro to ML
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฒ: Join AI Communities & Share Your Work
โ Join AI Discord servers, Reddit threads, and LinkedIn groups
โ Post your projects on GitHub
โ Engage in AI hackathons, challenges, and build in public
Your network = Your next opportunity.
๐ฏ ๐ฌ๐ผ๐๐ฟ ๐๐ถ๐ฟ๐๐ ๐๐ ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐ = ๐ฌ๐ผ๐๐ฟ ๐๐ป๐๐ฟ๐ ๐ฃ๐ผ๐ถ๐ป๐
Itโs not about knowing everythingโitโs about starting.
Consistency will compound.
Youโll go from โbeginnerโ to โbuilderโ faster than you think.
Free Artificial Intelligence Resources: https://whatsapp.com/channel/0029VaoePz73bbV94yTh6V2E
#ai
โค2๐ฅ1
Forwarded from Artificial Intelligence
๐ ๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ผ๐บ๐ฝ๐๐๐ฒ๐ฟ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ณ๐ฟ๐ผ๐บ ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ, ๐ฆ๐๐ฎ๐ป๐ณ๐ผ๐ฟ๐ฑ, ๐ ๐๐ง & ๐๐ผ๐ผ๐ด๐น๐ฒ๐
Why pay thousands when you can access world-class Computer Science courses for free? ๐
Top institutions like Harvard, Stanford, MIT, and Google offer high-quality learning resources to help you master in-demand tech skills๐จโ๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3ZyQpFd
Perfect for students, self-learners, and career switchersโ ๏ธ
Why pay thousands when you can access world-class Computer Science courses for free? ๐
Top institutions like Harvard, Stanford, MIT, and Google offer high-quality learning resources to help you master in-demand tech skills๐จโ๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3ZyQpFd
Perfect for students, self-learners, and career switchersโ ๏ธ
Why learn SQL if ChatGPT can write it?
A few reasons why you should still learn SQL:
1๏ธโฃ An understanding of the nuances of SQL is necessary to ask the Large Language Model (โLLMโ) the right questions to get a good response.
2๏ธโฃ You have to double check the LLMs response. Sometimes I get answers that uses features that have been deprecated (probably because the LLM was trained on older data). It still makes mistakes and overcomplicates problems.
3๏ธโฃ Making changes to the query requires an understanding of SQL. Without it, you might get stuck. It's important to understand the query's purpose.
So what do I use these LLMs for?
I find it a good starting point for syntax or query structure. Like โhow would I use a window function to get the latest record in a table?โ But it doesnโt understand my companyโs data models, table relationships, or business logic. This is where my SQL + business knowledge comes in.
A few reasons why you should still learn SQL:
1๏ธโฃ An understanding of the nuances of SQL is necessary to ask the Large Language Model (โLLMโ) the right questions to get a good response.
2๏ธโฃ You have to double check the LLMs response. Sometimes I get answers that uses features that have been deprecated (probably because the LLM was trained on older data). It still makes mistakes and overcomplicates problems.
3๏ธโฃ Making changes to the query requires an understanding of SQL. Without it, you might get stuck. It's important to understand the query's purpose.
So what do I use these LLMs for?
I find it a good starting point for syntax or query structure. Like โhow would I use a window function to get the latest record in a table?โ But it doesnโt understand my companyโs data models, table relationships, or business logic. This is where my SQL + business knowledge comes in.
โค1
ChatGPT Prompt to learn any skill
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(Tap on above text to copy)
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I am seeking to become an expert professional in [Making ChatGPT prompts perfectly]. I would like ChatGPT to provide me with a complete course on this subject, following the principles of Pareto principle and simulating the complexity, structure, duration, and quality of the information found in a college degree program at a prestigious university. The course should cover the following aspects: Course Duration: The course should be structured as a comprehensive program, spanning a duration equivalent to a full-time college degree program, typically four years. Curriculum Structure: The curriculum should be well-organized and divided into semesters or modules, progressing from beginner to advanced levels of proficiency. Each semester/module should have a logical flow and build upon the previous knowledge. Relevant and Accurate Information: The course should provide all the necessary and up-to-date information required to master the skill or knowledge area. It should cover both theoretical concepts and practical applications. Projects and Assignments: The course should include a series of hands-on projects and assignments that allow me to apply the knowledge gained. These projects should range in complexity, starting from basic exercises and gradually advancing to more challenging real-world applications. Learning Resources: ChatGPT should share a variety of learning resources, including textbooks, research papers, online tutorials, video lectures, practice exams, and any other relevant materials that can enhance the learning experience. Expert Guidance: ChatGPT should provide expert guidance throughout the course, answering questions, providing clarifications, and offering additional insights to deepen understanding. I understand that ChatGPT's responses will be generated based on the information it has been trained on and the knowledge it has up until September 2021. However, I expect the course to be as complete and accurate as possible within these limitations. Please provide the course syllabus, including a breakdown of topics to be covered in each semester/module, recommended learning resources, and any other relevant information(Tap on above text to copy)
โค2
๐๐ฒ๐ฎ๐ฟ๐ป ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐ณ๐ผ๐ฟ ๐๐ฟ๐ฒ๐ฒ ๐ผ๐ป ๐ฌ๐ผ๐๐ง๐๐ฏ๐ฒ โ ๐๐ผ๐บ๐ฝ๐น๐ฒ๐๐ฒ ๐ฃ๐น๐ฎ๐๐น๐ถ๐๐ ๐๐๐ถ๐ฑ๐ฒ๐
๐ฅ YouTube is the ultimate free classroomโand this is your Data Analytics syllabus in one post!๐จโ๐ป
From Python and SQL to Power BI, Machine Learning, and Data Science, these carefully curated playlists will take you from complete beginner to job-readyโจ๏ธ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4jzVggc
Enjoy Learning โ ๏ธ
๐ฅ YouTube is the ultimate free classroomโand this is your Data Analytics syllabus in one post!๐จโ๐ป
From Python and SQL to Power BI, Machine Learning, and Data Science, these carefully curated playlists will take you from complete beginner to job-readyโจ๏ธ๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4jzVggc
Enjoy Learning โ ๏ธ
โค1
How to get job as python fresher?
1. Get Your Python Fundamentals Strong
You should have a clear understanding of Python syntax, statements, variables & operators, control structures, functions & modules, OOP concepts, exception handling, and various other concepts before going out for a Python interview.
2. Learn Python Frameworks
As a beginner, youโre recommended to start with Django as it is considered the standard framework for Python by many developers. An adequate amount of experience with frameworks will not only help you to dive deeper into the Python world but will also help you to stand out among other Python freshers.
3. Build Some Relevant Projects
You can start it by building several minor projects such as Number guessing game, Hangman Game, Website Blocker, and many others. Also, you can opt to build few advanced-level projects once youโll learn several Python web frameworks and other trending technologies.
@crackingthecodinginterview
4. Get Exposure to Trending Technologies Using Python.
Python is being used with almost every latest tech trend whether it be Artificial Intelligence, Internet of Things (IOT), Cloud Computing, or any other. And getting exposure to these upcoming technologies using Python will not only make you industry-ready but will also give you an edge over others during a career opportunity.
5. Do an Internship & Grow Your Network.
You need to connect with those professionals who are already working in the same industry in which you are aspiring to get into such as Data Science, Machine learning, Web Development, etc.
Python Interview Q&A: https://topmate.io/coding/898340
Like for more โค๏ธ
ENJOY LEARNING ๐๐
1. Get Your Python Fundamentals Strong
You should have a clear understanding of Python syntax, statements, variables & operators, control structures, functions & modules, OOP concepts, exception handling, and various other concepts before going out for a Python interview.
2. Learn Python Frameworks
As a beginner, youโre recommended to start with Django as it is considered the standard framework for Python by many developers. An adequate amount of experience with frameworks will not only help you to dive deeper into the Python world but will also help you to stand out among other Python freshers.
3. Build Some Relevant Projects
You can start it by building several minor projects such as Number guessing game, Hangman Game, Website Blocker, and many others. Also, you can opt to build few advanced-level projects once youโll learn several Python web frameworks and other trending technologies.
@crackingthecodinginterview
4. Get Exposure to Trending Technologies Using Python.
Python is being used with almost every latest tech trend whether it be Artificial Intelligence, Internet of Things (IOT), Cloud Computing, or any other. And getting exposure to these upcoming technologies using Python will not only make you industry-ready but will also give you an edge over others during a career opportunity.
5. Do an Internship & Grow Your Network.
You need to connect with those professionals who are already working in the same industry in which you are aspiring to get into such as Data Science, Machine learning, Web Development, etc.
Python Interview Q&A: https://topmate.io/coding/898340
Like for more โค๏ธ
ENJOY LEARNING ๐๐
โค1
Forwarded from Artificial Intelligence
๐ฆ๐ค๐ ๐ญ๐ฌ๐ฌ% ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Looking to master SQL for Data Analytics or prep for your dream tech job? ๐ผ
These 3 Free SQL resources will help you go from beginner to job-readyโwithout spending a single rupee! ๐โจ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3TcvfsA
๐ฅ Start learning today and build the skills top companies want!โ ๏ธ
Looking to master SQL for Data Analytics or prep for your dream tech job? ๐ผ
These 3 Free SQL resources will help you go from beginner to job-readyโwithout spending a single rupee! ๐โจ
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3TcvfsA
๐ฅ Start learning today and build the skills top companies want!โ ๏ธ