10 際際滷 Intro to ML
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Its hard to imagine the frustration and helplessness a 65-year-old man with limited computer skills must feel when facing the aftermath of a crypto scam. Recovering a hacked trading wallet can feel like an absolute nightmare, especially when every step seems to lead you into an endless loop of failed solutions. Thats exactly what I went through over the past four weeks. After my trading wallet was compromised, the hacker changed my email address, password, and even removed my phone number from the account. For someone with little technical expertise, this was not just overwhelming, it was a disaster. Every suggested solution I came across in online help centers was either too complex or simply ineffective. I tried countless links, tutorials, and forums, only to find myself stuck, not even close to reclaiming my stolen crypto. In a last-ditch effort, I turned to Google and stumbled upon a review about MUYERN TRUST HACKER. At first, I was skeptical, like anyone would be in my position. But the glowing reviews, especially from people with similar experiences, gave me a glimmer of hope. Despite my doubts, I decided to reach out to them for assistance.The team at MUYERN TRUST HACKER immediately put me at ease. They were professional, understanding, and reassuring. Unlike other services that felt impersonal or automated, they took the time to walk me through every step of the recovery process. The fact that they were willing to schedule a 25-minute session to help me properly secure my account after recovery was invaluable. Today, Im grateful to say that my stolen crypto has been fully recovered, and my account is secure again. This experience has taught me that sometimes, even when you feel like all hope is lost, theres always a way to fight back. If youre going through something similar, dont give up. Reach out to MUYERN TRUST HACKER. Even if youve already tried everything, their expertise and persistence might just be the solution you need.I wholeheartedly recommend MUYERN TRUST HACKER to anyone facing the same situation. Whether youre a novice or experienced in technology, theyre the right team to trust when it comes to recovering stolen crypto or securing your accounts. Dont hesitate to contact them, it's worth it. Reach out to them on telegram at muyerntrusthackertech or web: ht tps :// muyerntrusthacker . o r g for faster response.
When Models Meet Data: From ancient science to todays Artificial Intelligence...
When Models Meet Data: From ancient science to todays Artificial Intelligence...ssuserbbbef4
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A presentation about Data and Machine Learning
Analyzing Consumer Spending Trends and Purchasing Behavior
Analyzing Consumer Spending Trends and Purchasing Behavioromololaokeowo1
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This project explores consumer spending patterns using Kaggle-sourced data to uncover key trends in purchasing behavior. The analysis involved cleaning and preparing the data, performing exploratory data analysis (EDA), and visualizing insights using ExcelI. Key focus areas included customer demographics, product performance, seasonal trends, and pricing strategies. The project provided actionable insights into consumer preferences, helping businesses optimize sales strategies and improve decision-making.Introduction to Generative Artificial Intelligence
Introduction to Generative Artificial IntelligenceLoic Merckel
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The buzz around Generative AI (GenAI) is louder than everbut are we seeing the whole picture?
This presentation was designed for a broad audience, avoiding technical jargon while addressing the real opportunities and challenges AI brings.
A few key insights from the presentation:
Innovation under constraint: DeepSeek achieved remarkable results at a fraction of competitors' costs.
The productivity paradox: AI may boost output for writers and coders but may reduce job satisfaction for scientists.
The shifting definition: "AI is what computers can't do; once they can, it's just software." Mustafa Suleyman
The GPU Bottleneck: Big Tech is turning to custom chips and nuclear energy to meet AI's soaring computational demands.
誌 Energy-Hungry AI: AI's energy needs are driving investments in dedicated nuclear power for datacenters.
際際滷 decks are meant to support live talks, so they might not capture the full story on their own. If you are curious to dive deeper, feel free to reach outI would be happy to discuss these ideas in a more interactive setting.
Feel free to check out the slides here and my LinkedIn post for further discussion: https://www.linkedin.com/posts/merckel_intro-to-genai-activity-7300095492862930946-rnL9Data Privacy presentation for companies.pptx
Data Privacy presentation for companies.pptxharmardir
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**Data Privacy Presentation**
**Introduction**
In the digital age, data privacy has become a crucial topic for individuals and organizations. As technology advances, the amount of personal and sensitive data being collected, stored, and processed continues to grow. Protecting this data from unauthorized access, breaches, and misuse is essential to maintaining trust and compliance with legal requirements.
**What is Data Privacy?**
Data privacy refers to the protection of personal and sensitive information from unauthorized access, use, or disclosure. It involves ensuring that individuals have control over how their data is collected, shared, and used. Data privacy is a fundamental right and plays a critical role in cybersecurity.
**Why is Data Privacy Important?**
1. **Protecting Personal Information:** Safeguarding data such as financial records, health information, and personal identifiers prevents identity theft and fraud.
2. **Regulatory Compliance:** Governments and international bodies have implemented strict data protection laws, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), to ensure companies handle data responsibly.
3. **Maintaining Trust:** Organizations that prioritize data privacy build trust with their customers and stakeholders, enhancing their reputation and credibility.
4. **Preventing Cyber Threats:** Cybercriminals often target personal and corporate data for financial gain. Strong data privacy measures reduce the risk of data breaches and cyberattacks.
**Key Data Privacy Regulations**
- **General Data Protection Regulation (GDPR):** Enforced in the European Union, GDPR sets strict guidelines on data collection, processing, and storage. It grants individuals rights over their personal data and imposes hefty fines for non-compliance.
- **California Consumer Privacy Act (CCPA):** A U.S.-based regulation that provides California residents with rights to know, delete, and opt out of the sale of their personal data.
- **Health Insurance Portability and Accountability Act (HIPAA):** Protects sensitive health information in the U.S.
- **Personal Data Protection Act (PDPA):** Enforces data protection measures in countries like Singapore.
**Challenges in Data Privacy**
1. **Growing Volume of Data:** With the rise of big data and cloud storage, managing and securing vast amounts of information is challenging.
2. **Evolving Cyber Threats:** Hackers continuously develop new methods to exploit vulnerabilities, making data security a constant battle.
3. **Lack of Awareness:** Many users and employees are unaware of best practices for protecting their data, leading to unintentional breaches.
4. **Compliance Complexity:** Different regulations across regions create difficulties for multinational organizations in ensuring full compliance.
**Best Practices for Data Privacy**
- **Data Encryption:** Encrypt sensitive information to protect it from unauthorized access.
- **Strong AuthentiIndustry_Use_Cases.ppt Industry_Use_Cases.ppt
Industry_Use_Cases.ppt Industry_Use_Cases.pptssuser3e8ddb
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Industry_Use_Cases.pptIndustry_Use_Cases.ppt
Plant Disease Prediction with Image Classification using CNN.pdf
Plant Disease Prediction with Image Classification using CNN.pdfTheekshana Wanniarachchi
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Plant diseases pose a significant threat to agricultural productivity. Early detection and classification of plant diseases can help mitigate losses. This project focuses on building a Plant Disease Prediction system using Convolutional Neural Networks (CNNs). The system leverages NumPy, TensorFlow, and Streamlit to develop a model and deploy a web-based application. The final model is also containerized using Docker for efficient deployment.
10 際際滷 Intro to ML
- 1. Introduction to Machine Learning NITESH SURANA INFORMATION TECHNOLOGY SECTION - A , ROLL NO. -55 DATE - 30.03.2017
- 2. What do you mean?
- 3. Formally A computer program is said to learn from experience (E) with some class of tasks (T) and a performance measure (P) if its performance at tasks in T as measured by P improves with E Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, it allows computers to find hidden insights without being explicitly programmed where to look.
- 4. Machine Learning Supervised Classification Regression Unsupervised Reinforcement Semi-Supervised
- 5. Supervised Learning Model preparation using training data If predictions are wrong, they are corrected The training process continues until the model achieves a desired level of accuracy on the training data. Some types Classification, Regression
- 6. Unsupervised Learning It is used against data that has no historical labels. The system is not told the "right answer." The algorithm must figure out what is being shown. A model is prepared by deducing structures present in the input data.
- 7. Where is ML?