Google AI Studio and Gemini API Now Support YouTube Video Links

Google has introduced YouTube video link support in Google AI Studio and the Gemini API, enabling developers to directly pass YouTube URLs to Gemini models. This enhancement allows the AI to process and understand video content without requiring manual downloading, conversion, or processing.

By simplifying video analysis, Google aims to improve efficiency for developers and further integrate its AI tools with content platforms.

Want to use ChatGPT at lightning speed?

You must tap in to ChatGPT's short cuts.

1. Go to ChatGPT
2. Bottom right '?' mark
3. Access keyboard shortcuts

Keyboard Shortcuts:

1. Show shortcuts: Ctrl + /
2. Focus chat input: Shift + Esc
3. Toggle sidebar: Ctrl + Shift + S
4. Open new chat: Ctrl + Shift + O
5. Copy last response: Ctrl + Shift + C

For example:

"Write a paper from ChatGPT's output."

1. Copy output: Ctrl + Shift + C
2. Open new chat: Ctrl + Shift + O
3. Ask it to write a paper on the info.
4. Ctrl V to paste in new information.
5. Press enter. Then paper completed.

(without ever touching your mouse)

Now THIS is ChatGPT mastery.

Move fast. Save time.

Can you use Chat GPT as a data analyst?

The answer to this question is yes, but you need to be cautious about using Chat GPT on the job (and even while learning analytics) for the following reasons.

1. Chat GPT gets things wrong. A lot.

If you use Chat GPT to write code, you better know that coding language extremely well, because you gotta be able to fact check and alter the response you get from Chat GPT.

For this reason, I would recommend staying away from Chat GPT when you’re learning SQL, Python, etc so you thoroughly learn the code without becoming dependent on AI.

2. You absolutely CANNOT paste company data into Chat GPT

As data analysts we work with highly confidential data that we must exercise great caution to protect.

For this reason, no matter how secure Chat GPT says it is, you must never paste company data into the application.

3. Some companies and bosses may not allow the use of Chat GPT

This is a reality in the world of tech and data since the avalanche of AI tools and features over the last couple years.

I’ve heard of some companies that block Chat GPT altogether, and some managers who advise against using it out of fears for security and other reasons.

Given all three of these reasons, feel free to play around with Chat GPT and AI and learn about them, but don’t become overly dependent on these tools.

🗣️ Geoffrey Hinton: AI will be wonderful for productivity, but it may not be wonderful for society. Because, in the current system, increased productivity benefits the rich and big companies, and ordinary people may suffer due to job losses

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Physicists think AI is physics.
Statisticians think AI is statistics.
Mathematicians think AI is mathematics.
Psychologists think AI is psychology.
Neuroscientists think AI is neuroscience.
And they’re all right.

Essential Data Analysis Techniques Every Analyst Should Know

1. Denoscriptive Statistics: Understanding measures of central tendency (mean, median, mode) and measures of spread (variance, standard deviation) to summarize data.

2. Data Cleaning: Techniques to handle missing values, outliers, and inconsistencies in data, ensuring that the data is accurate and reliable for analysis.

3. Exploratory Data Analysis (EDA): Using visualization tools like histograms, scatter plots, and box plots to uncover patterns, trends, and relationships in the data.

4. Hypothesis Testing: The process of making inferences about a population based on sample data, including understanding p-values, confidence intervals, and statistical significance.

5. Correlation and Regression Analysis: Techniques to measure the strength of relationships between variables and predict future outcomes based on existing data.

6. Time Series Analysis: Analyzing data collected over time to identify trends, seasonality, and cyclical patterns for forecasting purposes.

7. Clustering: Grouping similar data points together based on characteristics, useful in customer segmentation and market analysis.

8. Dimensionality Reduction: Techniques like PCA (Principal Component Analysis) to reduce the number of variables in a dataset while preserving as much information as possible.

9. ANOVA (Analysis of Variance): A statistical method used to compare the means of three or more samples, determining if at least one mean is different.

10. Machine Learning Integration: Applying machine learning algorithms to enhance data analysis, enabling predictions, and automation of tasks.

Like this post if you need more 👍❤️

Hope it helps :)

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