๐๐ฅ๐๐ ๐ง๐ฒ๐ฐ๐ต ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ง๐ผ ๐๐บ๐ฝ๐ฟ๐ผ๐๐ฒ ๐ฌ๐ผ๐๐ฟ ๐ฆ๐ธ๐ถ๐น๐น๐๐ฒ๐ ๐
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โค1
๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐ข๐ณ๐ณ๐ฒ๐ฟ๐ถ๐ป๐ด ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐
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Here are some essential data science concepts from A to Z:
A - Algorithm: A set of rules or instructions used to solve a problem or perform a task in data science.
B - Big Data: Large and complex datasets that cannot be easily processed using traditional data processing applications.
C - Clustering: A technique used to group similar data points together based on certain characteristics.
D - Data Cleaning: The process of identifying and correcting errors or inconsistencies in a dataset.
E - Exploratory Data Analysis (EDA): The process of analyzing and visualizing data to understand its underlying patterns and relationships.
F - Feature Engineering: The process of creating new features or variables from existing data to improve model performance.
G - Gradient Descent: An optimization algorithm used to minimize the error of a model by adjusting its parameters.
H - Hypothesis Testing: A statistical technique used to test the validity of a hypothesis or claim based on sample data.
I - Imputation: The process of filling in missing values in a dataset using statistical methods.
J - Joint Probability: The probability of two or more events occurring together.
K - K-Means Clustering: A popular clustering algorithm that partitions data into K clusters based on similarity.
L - Linear Regression: A statistical method used to model the relationship between a dependent variable and one or more independent variables.
M - Machine Learning: A subset of artificial intelligence that uses algorithms to learn patterns and make predictions from data.
N - Normal Distribution: A symmetrical bell-shaped distribution that is commonly used in statistical analysis.
O - Outlier Detection: The process of identifying and removing data points that are significantly different from the rest of the dataset.
P - Precision and Recall: Evaluation metrics used to assess the performance of classification models.
Q - Quantitative Analysis: The process of analyzing numerical data to draw conclusions and make decisions.
R - Random Forest: An ensemble learning algorithm that builds multiple decision trees to improve prediction accuracy.
S - Support Vector Machine (SVM): A supervised learning algorithm used for classification and regression tasks.
T - Time Series Analysis: A statistical technique used to analyze and forecast time-dependent data.
U - Unsupervised Learning: A type of machine learning where the model learns patterns and relationships in data without labeled outputs.
V - Validation Set: A subset of data used to evaluate the performance of a model during training.
W - Web Scraping: The process of extracting data from websites for analysis and visualization.
X - XGBoost: An optimized gradient boosting algorithm that is widely used in machine learning competitions.
Y - Yield Curve Analysis: The study of the relationship between interest rates and the maturity of fixed-income securities.
Z - Z-Score: A standardized score that represents the number of standard deviations a data point is from the mean.
Credits: https://t.me/free4unow_backup
Like if you need similar content ๐๐
A - Algorithm: A set of rules or instructions used to solve a problem or perform a task in data science.
B - Big Data: Large and complex datasets that cannot be easily processed using traditional data processing applications.
C - Clustering: A technique used to group similar data points together based on certain characteristics.
D - Data Cleaning: The process of identifying and correcting errors or inconsistencies in a dataset.
E - Exploratory Data Analysis (EDA): The process of analyzing and visualizing data to understand its underlying patterns and relationships.
F - Feature Engineering: The process of creating new features or variables from existing data to improve model performance.
G - Gradient Descent: An optimization algorithm used to minimize the error of a model by adjusting its parameters.
H - Hypothesis Testing: A statistical technique used to test the validity of a hypothesis or claim based on sample data.
I - Imputation: The process of filling in missing values in a dataset using statistical methods.
J - Joint Probability: The probability of two or more events occurring together.
K - K-Means Clustering: A popular clustering algorithm that partitions data into K clusters based on similarity.
L - Linear Regression: A statistical method used to model the relationship between a dependent variable and one or more independent variables.
M - Machine Learning: A subset of artificial intelligence that uses algorithms to learn patterns and make predictions from data.
N - Normal Distribution: A symmetrical bell-shaped distribution that is commonly used in statistical analysis.
O - Outlier Detection: The process of identifying and removing data points that are significantly different from the rest of the dataset.
P - Precision and Recall: Evaluation metrics used to assess the performance of classification models.
Q - Quantitative Analysis: The process of analyzing numerical data to draw conclusions and make decisions.
R - Random Forest: An ensemble learning algorithm that builds multiple decision trees to improve prediction accuracy.
S - Support Vector Machine (SVM): A supervised learning algorithm used for classification and regression tasks.
T - Time Series Analysis: A statistical technique used to analyze and forecast time-dependent data.
U - Unsupervised Learning: A type of machine learning where the model learns patterns and relationships in data without labeled outputs.
V - Validation Set: A subset of data used to evaluate the performance of a model during training.
W - Web Scraping: The process of extracting data from websites for analysis and visualization.
X - XGBoost: An optimized gradient boosting algorithm that is widely used in machine learning competitions.
Y - Yield Curve Analysis: The study of the relationship between interest rates and the maturity of fixed-income securities.
Z - Z-Score: A standardized score that represents the number of standard deviations a data point is from the mean.
Credits: https://t.me/free4unow_backup
Like if you need similar content ๐๐
โค1
AI Side Hustles Cheat Sheet ๐ต
This cheat sheet is a quick reference guide designed to help you implement key strategies for
launching profitable AI side hustles. Whether it's creating content, selling products, or offering
services, AI tools make it easier to start generating income.
1. Why Now is the Best Time to Start an AI Side Hustle
- Since the release of ChatGPT in November 2022, AI has grown significantly across many
industries.
- AI tools can save time and effort, helping you launch side hustles quickly.
- Identify the best AI-powered side hustle for your goals and take action.
2. Create a Faceless YouTube Channel using AI Tools
- Benefits: A faceless YouTube channel allows you to create content without being on camera.
- Use ChatGPT to identify profitable niches for your channel.
- Create visuals and branding with AI tools like MidJourney or Canva AI.
- Use ChatGPT to brainstorm video topics and generate scripts.
- Use tools like InVideo.io to create videos from your scripts.
- Optimize your videos for YouTube SEO and promote them on social media.
3. Create a Profitable Online Course with AI Tools
- Use ChatGPT to find high-demand niches and sub-niches.
- Use ChatGPT to develop course outlines and video scripts.
- Create course videos using AI tools like elai.io.
- Select a platform (e.g., Teachable, Udemy) to launch and promote your course.
4. Sell Profitable Etsy Printables Created with AI Tools
- There is a growing demand for digital printables like planners, clipart, and wedding stationery
on Etsy.
- Conduct market research to identify profitable printable categories.
- Use AI tools like MidJourney or Canva to create unique designs.
- Use ChatGPT to generate new product ideas and optimize product descriptions.
- Set up and optimize your Etsy shop for visibility and sales.
5. Publish Children's Story Books with AI Tools on Amazon
- Children's storybooks are in demand on Amazon.
- Research popular genres and trends using Amazon KDP.
- Use ChatGPT to generate story ideas and develop narratives.
- Create illustrations using AI art tools.
- Format and upload your book to Amazon KDP, then optimize and promote it.
6. Leverage AI Tools for Profitable Affiliate Marketing
- Research and select profitable affiliate offers to promote.
- Use ChatGPT to create content for PDFs or blogs that promote your offer.
- Design engaging materials with Canva.
- Find the best platforms for distributing your affiliate marketing content, and optimize listings for
better conversions.
7. Offer Copywriting Services with AI Assistance
- Offer services such as product descriptions, email campaigns, and ad copy creation using AI
tools.
- Use ChatGPT to generate high-converting copy quickly and efficiently.
- Promote your copywriting services on platforms like Fiverr, Upwork, or freelancing websites.
This cheat sheet is a quick reference guide designed to help you implement key strategies for
launching profitable AI side hustles. Whether it's creating content, selling products, or offering
services, AI tools make it easier to start generating income.
1. Why Now is the Best Time to Start an AI Side Hustle
- Since the release of ChatGPT in November 2022, AI has grown significantly across many
industries.
- AI tools can save time and effort, helping you launch side hustles quickly.
- Identify the best AI-powered side hustle for your goals and take action.
2. Create a Faceless YouTube Channel using AI Tools
- Benefits: A faceless YouTube channel allows you to create content without being on camera.
- Use ChatGPT to identify profitable niches for your channel.
- Create visuals and branding with AI tools like MidJourney or Canva AI.
- Use ChatGPT to brainstorm video topics and generate scripts.
- Use tools like InVideo.io to create videos from your scripts.
- Optimize your videos for YouTube SEO and promote them on social media.
3. Create a Profitable Online Course with AI Tools
- Use ChatGPT to find high-demand niches and sub-niches.
- Use ChatGPT to develop course outlines and video scripts.
- Create course videos using AI tools like elai.io.
- Select a platform (e.g., Teachable, Udemy) to launch and promote your course.
4. Sell Profitable Etsy Printables Created with AI Tools
- There is a growing demand for digital printables like planners, clipart, and wedding stationery
on Etsy.
- Conduct market research to identify profitable printable categories.
- Use AI tools like MidJourney or Canva to create unique designs.
- Use ChatGPT to generate new product ideas and optimize product descriptions.
- Set up and optimize your Etsy shop for visibility and sales.
5. Publish Children's Story Books with AI Tools on Amazon
- Children's storybooks are in demand on Amazon.
- Research popular genres and trends using Amazon KDP.
- Use ChatGPT to generate story ideas and develop narratives.
- Create illustrations using AI art tools.
- Format and upload your book to Amazon KDP, then optimize and promote it.
6. Leverage AI Tools for Profitable Affiliate Marketing
- Research and select profitable affiliate offers to promote.
- Use ChatGPT to create content for PDFs or blogs that promote your offer.
- Design engaging materials with Canva.
- Find the best platforms for distributing your affiliate marketing content, and optimize listings for
better conversions.
7. Offer Copywriting Services with AI Assistance
- Offer services such as product descriptions, email campaigns, and ad copy creation using AI
tools.
- Use ChatGPT to generate high-converting copy quickly and efficiently.
- Promote your copywriting services on platforms like Fiverr, Upwork, or freelancing websites.
โค2
Forwarded from Artificial Intelligence
๐ฆ๐๐ฎ๐ฟ๐ ๐ฎ ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ ๐ถ๐ป ๐๐ฎ๐๐ฎ ๐ผ๐ฟ ๐ง๐ฒ๐ฐ๐ต (๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ด๐ถ๐ป๐ป๐ฒ๐ฟ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐ฎ๐๐ต)๐
Dreaming of a career in data or tech but donโt know where to begin?๐จโ๐ป๐
Donโt worry โ this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! ๐ป๐ผ
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Dreaming of a career in data or tech but donโt know where to begin?๐จโ๐ป๐
Donโt worry โ this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! ๐ป๐ผ
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โค1
Artificial Intelligence on WhatsApp ๐
Top AI Channels on WhatsApp!
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Top AI Channels on WhatsApp!
1. ChatGPT โ Your go-to AI for anything and everything. https://whatsapp.com/channel/0029VapThS265yDAfwe97c23
2. OpenAI โ Your gateway to cutting-edge artificial intelligence innovation. https://whatsapp.com/channel/0029VbAbfqcLtOj7Zen5tt3o
3. Microsoft Copilot โ Your productivity powerhouse. https://whatsapp.com/channel/0029VbAW0QBDOQIgYcbwBd1l
4. Perplexity AI โ Your AI-powered research buddy with real-time answers. https://whatsapp.com/channel/0029VbAa05yISTkGgBqyC00U
5. Generative AI โ Your creative partner for text, images, code, and more. https://whatsapp.com/channel/0029VazaRBY2UPBNj1aCrN0U
6. Prompt Engineering โ Your secret weapon to get the best out of AI. https://whatsapp.com/channel/0029Vb6ISO1Fsn0kEemhE03b
7. AI Tools โ Your toolkit for automating, analyzing, and accelerating everything. https://whatsapp.com/channel/0029VaojSv9LCoX0gBZUxX3B
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9. Google Gemini โ Generate images & videos with AI. https://whatsapp.com/channel/0029Vb5Q4ly3mFY3Jz7qIu3i/103
10. Data Science & Machine Learning โ Your fuel for insights, predictions, and smarter decisions. https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
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โค4
Forwarded from Python Projects & Resources
๐๐๐ฆ๐๐ข ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐๐
- Data Analytics
- Data Science
- Python
- Javascript
- Cybersecurity
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- Data Analytics
- Data Science
- Python
- Javascript
- Cybersecurity
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Most Asked SQL Interview Questions at MAANG Companies๐ฅ๐ฅ
Preparing for an SQL Interview at MAANG Companies? Here are some crucial SQL Questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
SELECT * FROM table_name;
2. What SQL statement is used to filter records?
SELECT * FROM table_name
WHERE condition;
The WHERE clause is used to filter records based on a specified condition.
3. How can you join multiple tables? Describe different types of JOINs.
SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;
Types of JOINs:
1. INNER JOIN: Returns records with matching values in both tables
SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;
2. LEFT JOIN: Returns all records from the left table & matched records from the right table. Unmatched records will have NULL values.
SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;
3. RIGHT JOIN: Returns all records from the right table & matched records from the left table. Unmatched records will have NULL values.
SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;
4. FULL JOIN: Returns records when there is a match in either left or right table. Unmatched records will have NULL values.
SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;
4. What is the difference between WHERE & HAVING clauses?
WHERE: Filters records before any groupings are made.
SELECT * FROM table_name
WHERE condition;
HAVING: Filters records after groupings are made.
SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;
5. How do you calculate average, sum, minimum & maximum values in a column?
Average: SELECT AVG(column_name) FROM table_name;
Sum: SELECT SUM(column_name) FROM table_name;
Minimum: SELECT MIN(column_name) FROM table_name;
Maximum: SELECT MAX(column_name) FROM table_name;
Here you can find essential SQL Interview Resources๐
https://t.me/mysqldata
Like this post if you need more ๐โค๏ธ
Hope it helps :)
Preparing for an SQL Interview at MAANG Companies? Here are some crucial SQL Questions you should be ready to tackle:
1. How do you retrieve all columns from a table?
SELECT * FROM table_name;
2. What SQL statement is used to filter records?
SELECT * FROM table_name
WHERE condition;
The WHERE clause is used to filter records based on a specified condition.
3. How can you join multiple tables? Describe different types of JOINs.
SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;
Types of JOINs:
1. INNER JOIN: Returns records with matching values in both tables
SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;
2. LEFT JOIN: Returns all records from the left table & matched records from the right table. Unmatched records will have NULL values.
SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;
3. RIGHT JOIN: Returns all records from the right table & matched records from the left table. Unmatched records will have NULL values.
SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;
4. FULL JOIN: Returns records when there is a match in either left or right table. Unmatched records will have NULL values.
SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;
4. What is the difference between WHERE & HAVING clauses?
WHERE: Filters records before any groupings are made.
SELECT * FROM table_name
WHERE condition;
HAVING: Filters records after groupings are made.
SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;
5. How do you calculate average, sum, minimum & maximum values in a column?
Average: SELECT AVG(column_name) FROM table_name;
Sum: SELECT SUM(column_name) FROM table_name;
Minimum: SELECT MIN(column_name) FROM table_name;
Maximum: SELECT MAX(column_name) FROM table_name;
Here you can find essential SQL Interview Resources๐
https://t.me/mysqldata
Like this post if you need more ๐โค๏ธ
Hope it helps :)
โค3
Forwarded from Artificial Intelligence
๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฅ๐๐ ๐ฅ๐ผ๐ฎ๐ฑ๐บ๐ฎ๐ฝ ,๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ,๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐ & ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐๐๐ถ๐ฑ๐ฒ๐
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โค1
Forwarded from Artificial Intelligence
๐๐ป๐ฑ๐๐๐๐ฟ๐ ๐๐ฝ๐ฝ๐ฟ๐ผ๐๐ฒ๐ฑ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ ๐
Whether youโre interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, thereโs something here for everyone.
โ 100% Free Courses
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Whether youโre interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, thereโs something here for everyone.
โ 100% Free Courses
โ Govt. Incentives on Completion
โ Self-paced Learning
โ Certificates to Showcase on LinkedIn & Resume
โ Mock Assessments to Test Your Skills
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Enroll for FREE & Get Certified ๐
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โค1