“Analyzing and Optimizing Conversion Rates: Decoding the Dynamics”

Introduction: Are you facing challenges in maximizing your e-commerce conversion rates? You’re not alone. Conversion Rates (CR) are the cornerstone of success in the digital marketplace. This article is your go-to guide for understanding and leveraging essential metrics and Key Performance Indicators (KPIs) to elevate your e-commerce performance. We’ll explore strategies to decode the dynamics … Read more

Quantitative Investing, Recommendation Engines, and Poker: Crafting a Strategy 

Diving into the world of quantitative investing, recommendation engine design, and poker gameplay has become a fascinating journey for me recently. My quest involves not only comprehending these seemingly disparate subjects but also finding ways to leverage them profitably. It was during a recent poker event in Cyprus, as I relished the games that a … Read more

Recommendation built by engineers vs. Recommendation built by scientists

Welcome to this exploration of the world of recommendation engines, where we’ll dive into the crucial aspect of modeling recommendation problems and the profound impact they can have on the results. In this blog post, I’ll share insights from my journey and experiences, highlighting instances where the right modeling strategy made all the difference. But … Read more

Customer Segmentation is not clustering!

Introduction: Customer segmentation is a fascinating task that empowers businesses to gain deeper insights into their customers and better understand their data and operations. The ability to comprehend customers and deliver personalized services is an invaluable asset that no one can deny. Businesses of all scales and stages in their journey use customer segmentation to … Read more

Creativity: Systematic Determinism or Individual Ingenuity

Introduction:

In a world where remarkable ideas seem to emerge independently in different minds and cultures, we are faced with the intriguing question of whether creativity is a mere coincidence or a product of systematic forces at play. To illustrate this conundrum, let me share a personal experience. Back in 2015, I stumbled upon an invitation poster for an event called Ideabazaar, where participants were invited to present their startup ideas in the realm of cosmetics and beauty products. I decided to participate and thought to combine my AI skills with the competition context, which was cosmetics and beauty; I conceived the idea of a “Beauty Mirror” app, utilizing computer vision technology to test cosmetics on users’ faces virtually. Surprisingly, I later discovered that a company in Canada and other locations was already working on the same idea independently. This recurring phenomenon of simultaneous idea generation raises the question: Is there a systematic process guiding creativity, or is it solely driven by individual minds?

Sephora using augmented reality for test lipsticks

 

The Recurring Phenomenon:

The example of the Beauty Mirror app is not an isolated incident; throughout history, numerous instances demonstrate the simultaneous emergence of identical or similar ideas in diverse geographical regions without any apparent interaction. This recurring phenomenon might appear coincidental, but it challenges us to consider the possibility of a systematic process underlying creativity.

Examining ancient myths and legends offers another intriguing perspective on this matter. For instance, the stories of the Simurgh in Eastern cultures and the Phoenix in Western cultures share astonishingly similar structures and functionalities. How could these distinct civilizations independently create such similar mythical creatures? This leads us to question whether these ideas were products of the collective societal consciousness rather than individual minds.

simurgh
Phoenix
Society as the Arbiter of Creativity:

In this view, society and civilization play pivotal roles in shaping ideas and creative outputs. Individuals, in turn, act as conduits for these occurrences, translating societal influences into tangible creations. We can consider a computer as a society generating and processing information, and individuals become the outlets and ports for the forces and directions set forth.

If we entertain this hypothesis, it poses thought-provoking implications for our worldview. One significant consideration is that society, in its current state, influences individuals to create ideas and innovations according to their own needs and directions. Consequently, society determines the course of progress and invention, while individuals become the vessels through which these developments manifest.

By embracing this perspective, we might conclude that even if humanity were to start afresh numerous times, our collective progress would likely converge toward similar outcomes. Technological advancements, cultural nuances, knowledge dissemination, religious beliefs, and political structures would, to a large extent, remain consistent. Furthermore, this perspective invites us to reconsider the role of celebrated historical figures often deemed the initiators of significant ideas and inventions. Without these individuals, it is conceivable that other capable minds would have brought forth these innovations, and history would recognize them as the originators. Not even the brilliant ideas, even the horrible criminals, may be repeated. Names like Edison, Einstein, Khayam, Hitler, etc., wouldn’t appear, but some other names with the same idea may be introduced.

In pondering the interplay between systematic determinism and individual creativity, I unveil a complex relationship that challenges traditional notions of inspiration and innovation. While this hypothesis cannot be unequivocally proven, it prompts us to reassess the interconnected nature of society and individuality. Understanding this dynamic may pave the way for a fresh perspective on creativity, its origins, and its ultimate impact on the course of human history.

In the end, let’s consider an interesting scenario. Suppose in a society where humans are replaced by robots and AI, what happens to interplay between determinism and creativity? Let’s see what chatGPT answers:

In a society where humans are replaced by robots and AI, the interplay between determinism and creativity might undergo significant changes, leading to a redefined trade-off between these two aspects:

  1. Increased Determinism: With AI and robots assuming key roles in decision-making and problem-solving, the deterministic nature of these systems could become more pronounced. AI algorithms are designed to follow specific rules and logical processes, which could lead to a society with a higher degree of predictability and efficiency.
  2. Predictive Innovation: AI’s data-driven nature enables it to analyze vast amounts of information and patterns, making it proficient at predicting future trends and potential innovations. This predictive capability might lead to systematic innovation, as AI can anticipate societal needs and develop solutions proactively.
  3. Loss of Serendipity: Human creativity often thrives on serendipity, the accidental discovery of unexpected ideas. In a society dominated by AI, the element of chance and spontaneous creativity may diminish, as AI operates within defined parameters and logical rules.
  4. Reduced Individual Creativity: In a world where AI plays a central role in generating ideas and problem-solving, individual human creativity might take a backseat. With AI systems handling complex tasks, there could be less incentive for individuals to actively engage in creative pursuits

 

“Art of problem solving with data” Course

 

In the fast-paced world of data science and artificial intelligence (AI), it’s easy for newcomers to fall into the trap of focusing solely on algorithms and tools, neglecting the fundamental aspects of problem-solving. Recognizing this gap, a group of dedicated individuals came together to create a course that dives deeper into the untold issues of the data science field. Titled “Art of Problem Solving with Data,” this course aims to equip learners with the necessary skills to approach problems more comprehensively and effectively. Published on maktabkhoone.org, this course promises to elevate your understanding of data science beyond superficial knowledge.

  • Problem Statement: The course begins by emphasizing correctly addressing a problem. Students learn how to define problems, model them, and how to evaluate their solutions. Key topics covered include modularization, root cause analysis, and exploratory data analysis (EDA). By delving into these foundational elements, learners gain a perspective that extends beyond the mere application of algorithms. Understanding how to frame and analyze problems properly is crucial for success in data science.
  • Before Fit, After Predict: This course section focuses on the steps researchers should consider before and after applying machine learning techniques to solve a problem. While algorithms play a significant role, the course highlights the importance of thorough data preparation, feature engineering, and evaluation of models. Learners gain a comprehensive understanding of the entire data science pipeline by illuminating these oft-overlooked aspects. Being mindful of the entire process enables researchers to make informed decisions and achieve more reliable and robust results.
  • Data Storytelling: In this section, the course delves into data visualization tools and techniques, empowering learners to present and report results in a more accurate, concise, and compelling manner. By mastering the art of data storytelling, students enhance their ability to convey insights to diverse audiences. Captivating visuals help make complex information accessible and facilitate better decision-making, making this section invaluable for aspiring data scientists.

 

 

The “Art of Problem Solving with Data” course, published on maktabkhoone.org (, addresses the critical yet often overlooked aspects of data science. This course provides a well-rounded education that transcends the algorithm-centric approach by focusing on problem statements, the importance of steps before and after applying machine learning techniques, and data storytelling. While the course assumes a background in ML, AI, and data science, it is a valuable resource for those seeking a deeper understanding of the field. Leap and enroll in this course to gain the skills and knowledge necessary to excel in data science.

P.S: The Course presented in the Farsi language

Link to the course: Art of Problem Solving with Data

Feasibility of Arbitrary Return

As a Data Scientist, when I started working on quantitative trading at Eveince, my biggest problem was quantifying the problem’s objective function. One way is to set a KPI and evaluate the performance accordingly. However, KPI definition is the challenging part in addition to finding a model that satisfies it. The beauty of this problem is … Read more

Delta Beta instead of Success Rate

Introduction The success rate is a famous and practical metric used in numerous data science and AI applications and research. Due to its simplicity, Quant researchers also like to use this metric to evaluate their models and strategies, as we used it to assess the feasibility of arbitrary return. However, The success rate has some limitations. … Read more