by jsendak | Nov 1, 2024 | DS Articles
Image by Malachi Witt from Pixabay I had the chance to listen to a talk that Ivan Lee, Founder and CEO of Datasaur, gave during October 2024’s AI Summit here at the Computer History Museum in Mountain View, CA. Datasaur is an AWS partner and marketplace seller. One of the things Lee and company have… Read More »What to consider when selecting a learning model
The Future of Learning Models: Insights from Datasaur’s CEO
October 2024 witnessed an enthusiastic speech at the AI Summit from Ivan Lee, the Founder and CEO of Datasaur – an AWS partner and a market seller in the prospering industry of data science and analytics. Distilling his words, we look into the long-term implications and predict the possible future developments for learning models within the AI landscape.
Key Points
Though unfortunately, the full content of the speech wasn’t provided in the summarized text, the information about Lee’s position and his company’s role in the AI and data analytics landscape potentially offer valuable insights. As an AWS partner and a market seller, Datasaur’s perspective on learning models suggests the significance of scalability, flexibility and accuracy in AI-driven applications in the near future.
Future Developments
The technology world has always been fast-paced, especially when it comes to AI and machine learning. The influence of Lee’s company and the space it exists in reveal several key trends that are likely to shape AI’s future.
- Increased Demand for Scalability: As more businesses find themselves reliant on AI systems, there will be an increase in the demand for models that can scale effectively, allowing for simultaneous handling of multiple operations.
- Need for Flexibility:Data often comes in different forms and formats. Lessons from Datasaur specify importance of flexible learning models that can accommodate and process various types of data.
- Heightened Importance of Accuracy: As AI plays a more central role in business operations, its accuracy becomes more critical to the business’ bottom line. The demand for more accurate learning models is likely to surge.
Long Term Implications
These key trends come with long-term implications. The demand for scalable, flexible and accurate learning models shifts the focus towards advanced research and development in the field of AI and machine learning. Organizations and companies, like Datasaur, will need to invest significantly in R&D, ultimately driving further technological advancements.
Actionable Advice for Businesses
- Adopt Flexibility: Businesses must seek out learning models that can process a variety of data types, thus catering to the diverse needs of any organization.
- Scale Wisely: As businesses grow, it’s essential they utilize scalable learning models that can grow with them.
- Strive for Accuracy: Implementing learning models which prioritize accuracy can be crucial for delivering precise insights and making sound decisions.
- Invest in Research: With the changing AI landscape, businesses need to consider investing in research and development to stay ahead of the market and maintain competitiveness.
“The AI landscape is evolving rapidly. Businesses must not only adapt to these changes, but proactively strive for progress”
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by jsendak | Oct 31, 2024 | DS Articles
You can now obtain insights from your tabular data by chatting with it in techtonique.net. No plotting yet (coming soon), but you can already ask questions like:
- What is the average of column
A?
- Show me the first 5 rows of data
- Show me 5 random rows of data
- What is the sum of column
B?
- What is the average of column
A grouped by column B?
- …
As a reminder:
Techtonique web app, a tool designed to help you make informed, data-driven decisions using Mathematics, Statistics, Machine Learning, and Data Visualization. As of September 2024, the tool is in its beta phase (subject to crashes) and will remain completely free to use until December 24, 2024.
After registering, you will receive an email. CHECK THE SPAMS.
A few selected users will be contacted directly for feedback, but you can also send yours.
The tool is built on Techtonique and the powerful Python ecosystem. At the moment, it focuses on small datasets, with a limit of 1MB per input. Both clickable web interfaces and Application Programming Interfaces (APIs, see below) are available.
Currently, the available functionalities include:
- Data visualization. Example: Which variables are correlated, and to what extent?
- Probabilistic forecasting. Example: What are my projected sales for next year, including lower and upper bounds?
- Machine Learning (regression or classification) for tabular datasets. Example: What is the price range of an apartment based on its age and number of rooms?
- Survival analysis, analyzing time-to-event data. Example: How long might a patient live after being diagnosed with Hodgkin’s lymphoma (cancer), and how accurate is this prediction?
- Reserving based on insurance claims data. Example: How much should I set aside today to cover potential accidents that may occur in the next few years?
As mentioned earlier, this tool includes both clickable web interfaces and Application Programming Interfaces (APIs).
APIs allow you to send requests from your computer to perform specific tasks on given resources. APIs are programming language-agnostic (supporting Python, R, JavaScript, etc.), relatively fast, and require no additional package installation before use. This means you can keep using your preferred programming language or legacy code/tool, as long as it can speak to the internet. What are requests and resources?
In Techtonique/APIs, resources are Statistical/Machine Learning (ML) model predictions or forecasts.
A common type of request might be to obtain sales, weather, or revenue forecasts for the next five weeks. In general, requests for tasks are short, typically involving a verb and a URL path — which leads to a response.
Below is an example. In this case, the resource we want to manage is a list of users.
– Request type (verb): GET
- URL Path:
http://users | Endpoint: users | API Response: Displays a list of all users
- URL Path:
http://users/:id | Endpoint: users/:id | API Response: Displays a specific user
– Request type (verb): POST
- URL Path:
http://users | Endpoint: users | API Response: Creates a new user
– Request type (verb): PUT
- URL Path:
http://users/:id | Endpoint: users/:id | API Response: Updates a specific user
– Request type (verb): DELETE
- URL Path:
http://users/:id | Endpoint: users/:id | API Response: Deletes a specific user
In Techtonique/APIs, a typical resource endpoint would be /MLmodel. Since the resources are predefined and do not need to be updated (PUT) or deleted (DELETE), every request will be a POST request to a /MLmodel, with additional parameters for the ML model.
After reading this, you can proceed to the /howtoapi page.
Continue reading: Chat with your tabular data in www.techtonique.net
Techtonique.net: A New Horizon in Data Manipulation
Tabular data analysis has taken a significant turn with the recent introduction of Techtonique.net. This innovative data platform allows users to obtain crucial insights from their tabular data using an intuitive chat function. The tool, currently in its beta phase, is designed to facilitate data-driven decision-making using multiple disciplines including Mathematics, Statistics, Machine Learning, and Data Visualization.
Key Features and Functionalities
The web-based Techtonique application brings a wide range of practical functionalities to its users. Apart from getting insights from data chat, users can run R or Python code interactively in their browser. However, the application currently focuses on small datasets with a limit of 1MB per input.
Data Visualization
Data visualization is a built-in option where users can identify correlations between variables through graphical presentations.
Probabilistic Forecasting
Probabilistic forecasting is another attractive feature that allows users to predict future sales, including lower and upper bounds.
Machine Learning and Survival Analysis
Machine Learning and Survival Analysis add an extra layer to the platform by offering in-depth analysis options based on specific datasets – from predicting the price range of apartments to estimating a life insurance payout.
The Working Principles: Interactive Web Interfaces & API
Both interactive web interfaces and Application Programming Interfaces (APIs) drive the functionality in Techtonique. APIs add versatility to the platform by allowing users to send requests to perform tasks on given resources. This flexible usage is not restricted to a specific programming language and thus, supports Python, R, JavaScript, and more.
Future Developments and Long-term Implications
As Techtonique.net is still in the beta phase, one can anticipate potential updates and advancements in future releases. An evident shortcoming at this stage is the absence of a plotting function – the inclusion of which will significantly enhance the data visualization aspect of the tool. The current limit on dataset size (1MB per input) may also be addressed, offering a wider scope for large-data analysis.
In the long-term, Techtonique.net may have a profound influence on data-driven industries, creating a more convenient and efficient system for data analysis. The impact could be particularly significant within organizations dealing with large-scale data, potentially enhancing their decision-making processes and operational efficiency.
Actionable Advice
To fully utilize the potential of this cutting-edge tool, users should:
- Get Familiar with the Functionality: Understand how to use the platform’s features – from running R or Python, to using the data chat capability.
- Keep up with Updates: As Techtonique.net is in the beta phase, there may be frequent updates and additions – all of which could lead to improved user experience.
- Provide Feedback: Be an active contributor to the system’s development by providing feedback and suggestions. Your insights could guide future enhancements and make the tool more robust and user-friendly.
- Experiment with Different Technologies: The tool supports several programming languages. Therefore, use this versatile platform to enhance your skills with Python, R, and JavaScript.
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by jsendak | Oct 31, 2024 | DS Articles
Pursue career success with big savings on edX programs using code EDXSUCCESS24 at checkout.
Long-Term Implications and Future Developments of Online Education
Technology has revolutionized education in many ways, bringing learning opportunities right at the click of a button. The recent promotional offer shared by edX, using the code EDXSUCCESS24, emphasizes the growing popularity of online education platforms. This new wave in education has great potential long-term societal and economic implications. Also, there are innovative developments expected in the future.
Long-Term Implications of Online Education
- Greater accessibility and inclusivity: With online platforms such as edX, education is no longer limited to traditional classrooms and those who can afford to attend universities. This creates a far more inclusive learning environment catering to individuals worldwide.
- Flexible learning: Online education offers the flexibility of learning at one’s own pace in their chosen environment. This is ideal for adult learners, working professionals, and students who prefer self-paced learning.
- Cost-effective education: Promotional deals like these offered by edX make quality education more affordable. In the long run, this could heavily influence the democratisation of education.
- Career enhancement: Online platforms provide a great opportunity for upskilling or reskilling. It aids individuals in advancing their careers or transitioning into a new field.
Future Developments
- Innovative teaching methods: Future developments in online education may include increased use of virtual reality, augmented reality, and AI in teaching methods.
- Personalized learning: Advanced analytics and adaptive learning systems could tailor education to individual needs and preferences, making learning more effective.
- Collaboration: Future developments might focus on improving interaction, allowing students to collaborate, brainstorm and communicate virtually.
Actionable Advice
Here is some advice that learners can leverage to advantageously utilise offers like EDXSUCCESS24.
- Research about the course and its content before enrolling. Make sure it aligns with your career aspirations or learning goals.
- Manage your time wisely. Although online education provides flexibility, maintaining discipline is essential for successful completion.
- Utilize collaborative features like discussion forums. They provide an excellent platform for asking questions, exchanging knowledge, and networking.
Indeed, online platforms like edX are not just transforming the realm of education but also making it more accessible, interactive, affordable – in essence, democratizing it. As we move further into this digital age, virtual learning will continue to evolve and enhance the way we learn.
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by jsendak | Oct 31, 2024 | DS Articles
LLM Chunking, Indexing, Scoring and Agents, in a Nutshell. The new PageRank of RAG/LLM. With details on building relevancy scores.
Unpacking the Future of RAG/LLM’s New PageRank: Relevancy Scores, Chunking, Indexing, and Scoring
The recent move of introducing a new PageRank system by RAG/LLM is a significant development in the evolving landscape of digital marketing. Unraveling the importance of chunking, indexing, scoring, and agents in this mix is crucial for understanding its long-term implications and future potential.
Understanding the New PageRank of RAG/LLM
The new PageRank system represents a shift in the way digital content is ranked and viewed online. It’s characterized by an increased emphasis on relevancy scores. This shift towards relevancy is likely to result in more personalized and engaging experiences for internet users, making it more important than ever for content creators to match their offerings to their audience’s interests and needs.
Long-term Implications
Impact on Digital Marketing
The new PageRank system, with its emphasis on relevancy scores, represents a significant shift in the way businesses must approach digital marketing. Rather than simply aiming for high traffic volumes, the focus now should be on creating high-quality, relevant content that meets user needs and creates engagement.
Dominance of Data-Driven Strategies
This shift towards greater relevance also implies an increased reliance on big data and analytics. As the algorithm becomes more sophisticated, businesses will need to become more data-oriented and develop strategies around data insights.
Possible Future Developments
Scoring System Enhancement
With the advancements in technology and rise in data-driven marketing tactics, it’s predictable that RAG/LLM will continue to refine their scoring system. Enhanced capabilities may include real-time updates of scores or predictive scoring based on historical data.
Expanded Role of Agents
As the web becomes more complex, agents – applications that automatically gather and process information – will play an increasingly important role. Their duties may expand to include more comprehensive data gathering, processing, presentation, and decision-making, facilitating a more customized web experience.
Actionable Advice
- Focus on Relevance: In line with RAG/LLM’s shift towards relevancy, businesses should prioritize creating content that is relevant and valuable to their target audience.
- Invest in Data Analysis: As the importance of relevancy scoring becomes the norm, having a solid understanding of data analytics and interpretation will be crucial to business success.
- Leaning on Automation: Invest in sophisticated automation tools and agents. They can conduct efficient data gathering and conversion, facilitating deeper insights and enabling businesses to respond to the fast-paced world of digital marketing.
In conclusion, building a successful online strategy in the era of the new PageRank requires a solid understanding of relevancy scoring and the effective use of data and tools like agents. By staying ahead of these trends, businesses can fully leverage the power of digital marketing to reach and engage their target audience.
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by jsendak | Oct 30, 2024 | DS Articles
Introduction
Understanding how to manipulate variables and work with expressions is fundamental to becoming a proficient C programmer. In this comprehensive guide, we’ll explore compound operators, operator precedence, and typecasting – essential concepts that will elevate your C programming skills from basic to professional level.
Understanding Basic Assignment Operators
Before diving into complex operations, let’s refresh our knowledge of basic assignment operators. In C, the simple assignment operator (=) stores a value in a variable:
int x = 5; // Basic assignment
What Are Compound Operators?
Compound operators combine an arithmetic or bitwise operation with assignment. They provide a shorter and more elegant way to write common programming operations.
Common compound operators include:
- += (addition assignment)
- -= (subtraction assignment)
- *= (multiplication assignment)
- /= (division assignment)
- %= (modulus assignment)
int x = 10;
x += 5; // Equivalent to: x = x + 5
The Magic of Compound Assignment Operators
Compound operators offer several advantages: 1. More concise code 2. Potentially better performance 3. Reduced chance of typing errors
Example:
// Without compound operators
total = total + (price * quantity);
// With compound operators
total += price * quantity;
Order of Operations in C
Operator Precedence
C follows a strict hierarchy for operator precedence:
- Parentheses ()
- Unary operators (++, –, !)
- Multiplication, Division, Modulus (*, /, %)
- Addition, Subtraction (+, -)
- Assignment operators (=, +=, -=, etc.)
Example:
int result = 5 + 3 * 2; // Results in 11, not 16
int result2 = (5 + 3) * 2; // Results in 16
Associativity Rules
When operators have the same precedence, associativity determines the order of evaluation:
int a, b, c;
a = b = c = 5; // Right-to-left associativity
Typecasting in C
Implicit Type Conversion
C automatically converts data types when necessary:
int x = 5;
double y = 2.5;
double result = x + y; // x is implicitly converted to double
Explicit Type Conversion
You can force type conversion using casting:
int x = (int)3.14; // Explicitly convert double to int
Common Pitfalls with Operators
- Integer Division Truncation
int result = 5 / 2; // Results in 2, not 2.5
- Overflow Issues
int max = 2147483647;
max += 1; // Overflow occurs
Best Practices for Using Operators
- Use parentheses for clarity
- Be aware of type conversion implications
- Check for potential overflow
- Use compound operators when appropriate
Debugging Tips
- Print intermediate values
- Use debugger watch expressions
- Check for type mismatches
Real-world Applications
// Banking transaction example
float balance = 1000.0;
float interest_rate = 0.05;
balance *= (1 + interest_rate); // Apply interest
Your Turn!
Try solving this problem: Create a program that converts temperature from Celsius to Fahrenheit using compound operators.
Problem:
// Write your solution here
float celsius = 25.0;
// Convert to Fahrenheit using the formula: (C * 9/5) + 32
Solution:
float celsius = 25.0;
float fahrenheit = celsius;
fahrenheit *= 9.0/5.0;
fahrenheit += 32;
Quick Takeaways
- Compound operators combine arithmetic operations with assignment
- Order of operations follows strict precedence rules
- Typecasting can be implicit or explicit
- Always consider potential overflow and type conversion issues
- Use parentheses for clear, unambiguous expressions
Frequently Asked Questions
-
Q: What’s the difference between ++x and x++? A: ++x increments x before using its value, while x++ uses the value first, then increments.
-
Q: Can compound operators be used with pointers? A: Yes, pointer arithmetic works with compound operators.
-
Q: Why does integer division truncate decimal places? A: C performs integer division when both operands are integers.
-
Q: How can I avoid integer overflow? A: Use larger data types or check for overflow conditions.
-
Q: When should I use explicit type casting? A: Use it when you need precise control over type conversion or to prevent data loss.
Let’s Connect!
Did you find this guide helpful? Share it with fellow programmers and let us know your thoughts in the comments below! Follow us for more C programming tutorials and tips.
Continue reading: Powering Up Your Variables with Assignments and Expressions in C
Projection on the Future of C and Recommendations
The C Programming language has time-tested resilience and remains a fundamental language for developers. This article discussed many of its features, from basic assignment operators to compound operators, operator precedence, and best practices. Analyzing these points, we can discern how they could impact the future of C programming along with giving advice for program efficiency and debugging.
Long-term Implications
Having a strong understanding of fundamental C concepts like operators, their use, and possible pitfalls can lead to increased efficiency in writing code and significantly fewer errors. By adopting the use of compound operators, for example, programmers can not only reduce their code length but may also improve performance. This, in turn, may make C a more appealing language for high-intensive processing tasks, extending the longevity of C’s practical use.
Additionally, the nuances of typecasting, whether implicit or explicit, provide valuable flexibility and precision when writing in C. This understanding means developers can precisely control data conversion to avoid data losses and other issues. Potentially, this could make the C language a more popular choice for precise, mathematical, and scientific programming.
Future Developments
Despite being an older language, C continues to be popular due to its raw speed, practical features, and overall flexibility. As more programmers master these core principles, we may see an increase in the quality of C-based software development projects, driving further innovation in the field.
Notably, the mastery of compound operators can lead to considerable advances in C programming in the long term. Compound operators, if utilized well, can not only shorten program lines but also have significant effects on program performance. By reducing variable access and opening the door for compiler optimizations, these operators can be a key factor in writing optimized and efficient code in C.
Actionable Advice
For programmers to stay competitive with C, they must:
- Have a thorough grasp of operators. This understanding will serve as a foundation for writing efficient and maintainable C code.
- Understand the importance of operator precedence, as this can eliminate common errors and provide more predictable program behavior.
- Notice the potential for typecasting to prevent type conversion issues.
- Make constant use of compound operators for more concise code and potentially, enhanced performance.
- Always be aware of overflow issues, particularly with integer division and correctly anticipate these in code design.
- Adopt a robust debugging strategy, involving regular checks for type mismatch.
Only by keeping these points in mind can C programmers prepare themselves for the future and innovate within the language.
Overall, skills in C open up great possibilities for software development. C programmers continue to be invaluable assets in software houses, driving advances in many application areas from system software to game development.
References:
- C Programming: Absolute Beginners Guide, 3rd Edition
- https://www.geeksforgeeks.org/c-typecasting/
- https://www.geeksforgeeks.org/assignment-operators-in-c-c/
Conclusion
The ability to work with variables, expressions and manipulate them in C is a quintessential skill. A strong foundation in these areas affords much greater command of the C language. Keep your skill set continuously evolving and adapt to the language’s growth. Understanding each facet of these core concepts is the route to becoming a competent and professional C programmer.
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by jsendak | Oct 30, 2024 | DS Articles
Here are some useful Python one-liners for common data cleaning tasks.
Understanding the Long-Term Implications of Python One-Liners for Data Cleaning Tasks
As technology evolves, so does the crucial role of data in big decision making. In this regard, Python one-liners play a significant part in data cleaning tasks. They do not just promote efficiency but also greatly enhance the quality of data, making it a powerful tool for predicting future trends, facilitating key decision-making processes, and prompting significant technological advancements.
The Potential Long-Term Implications
In the long run, harnessing the power of Python one-liners for data cleaning tasks can create a profound change across several sectors, from business analytics to predictive modeling in artificial intelligence, and more.
Python one-liners can simplify the data cleaning process, cut down processing time, and enable data analysts to focus more on analyzing and interpreting the refined data rather than spending countless hours trying to tidy up a messy dataset. As a result, it can create meaningful changes in the productivity and effectiveness of work within sectors reliant on data.
Possible Future Developments
As the demand for data-driven insights continues to skyrocket, it is fair to predict that Python one-liners will evolve to become even more streamlined and powerful. Advanced AI and machine learning algorithms could be integrated within the Python environment to automate more complex data cleaning tasks.
In the future, we might see the emergence of Python one-liners that not only clean data but also intelligently analyze and organize the data based on predefined parameters, thus giving a new dimension to autonomous data cleaning and structure building.
Actionable Advice
-
Stay updated: Python’s capabilities are evolving rapidly. It’s important to stay updated with the latest trends and developments in Python programming to effectively incorporate Python one-liners into your regular data cleaning tasks.
-
Learn more about Python one-liners: They can greatly simplify your job. Try to understand their functions, and practice using them in your projects.
-
Integrate AI: As AI continues to penetrate different aspects of technology, consider its incorporation to help you automate data cleaning tasks more effectively. This will not only enhance your workflow but also generate more accurate results.
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