READING Articles

This concise reading material is designed to provide a comprehensive introduction to modern tools and technology. Begin with the blogs to familiarize yourself with the concepts, then use resources like your trusted GenAI GPT tool, Google, YouTube, and more to deepen your understanding and master the topics.

A new article published every week !

Escape velocity

Escape velocity refers to the velocity needed for an object to escape the gravitational pull and move into space. Now, let's draw an analogy with learning, up-skilling, and breaking barriers in personal development.

Escape velocity in the context of personal development involves overcoming the gravitational pull of comfort zones, laziness, and mediocrity.

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Pre-Industrial Revolution

Each tool or technology utilized today has emerged from a necessity within human civilization to simplify day-to-day life. As a result, PreProd Opnsrc Technology Blogs have been launched, drawing insights from all the industrial revolutions humanity has experienced thus far.

We have come a long way, from handcrafted goods to mass production, the innovations that sparked the industrial revolution drastically changed how people lived and worked.

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1st Industrial Revolution

As you embark on your career in this modern era of industry, reflect on the innovators who paved the way during the First Industrial Revolution. The steam engine, power loom, and other developments revolutionised manufacturing, transportation, communication, and more.

As you embark on your career in this modern era of industry, reflect on the innovators who paved the way during the First Industrial Revolution.

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2nd Industrial Revolution

The Second Industrial Revolution stands as one of the most transformative periods in human history, marked by unparalleled technological advancements, economic growth, and societal change.

Second Industrial Revolution remains a defining chapter in the story of human progress, leaving an enduring legacy that continues to shape the modern world.

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3rd Industrial Revolution

The Third Industrial Revolution marks a significant shift from its predecessors because it isn't driven by one big discovery like steam power or electricity, but by the coming together of several groundbreaking technologies. In our blog journey, we're about to dive deep into this revolution.

Third Industrial Revolution was a transformative era characterised by unprecedented technological advancements, economic disruptions, and societal transformations.

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4th Industrial Revolution

Fourth Industrial Revolution, also known as the "Industry 4.0" or 4IR, is marked by a fusion of the physical and digital worlds through interconnected digital technologies.

Fourth Industrial Revolution was a transformative era characterised by unprecedented technological advancements, economic disruptions, and societal transformations.

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5th Industrial Revolution ?

5IR builds upon the digital innovations of the Fourth Industrial Revolution (4IR), integrating advanced technologies such as artificial intelligence (AI), robotics, blockchain, and biotechnology with human-centered approaches to create a collaborative ecosystem.

The Fifth Industrial Revolution represents a paradigm shift towards a collaborative and human-centric technological future.

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Comparing all IRs

The fourth Industrial Revolutions progressed from mechanization (1IR), through mass production and electrification (2IR), to the rise of electronics and automation (3IR), culminating in digital and cyber-physical systems integration (4IR).

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Stages of AI

The progression of Artificial Intelligence (AI) can be described through five distinct stages, each representing significant advancements in capability and complexity.

The journey from rule-based systems to superintelligent AI represents a path of increasing complexity, capability, and potential impact.

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Top 10 Promising Tech

These technologies represent the forefront of innovation and are poised to transform industries and society over the next decade. As they mature, they will drive economic growth, enhance quality of life, and address global challenges such as climate change and healthcare.

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Predicting the most promising technologies for the next decade involves analysing current trends, research, and potential impacts on various industries.

5Vs of data

The "5 Vs of Data" framework is commonly used to describe the key dimensions of big data. Understanding these dimensions helps in managing, analyzing, and leveraging large datasets effectively.

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Understanding and addressing five dimensions helps organizations manage big data effectively, turning raw data into valuable insights that drive decision-making and innovation.

Data the newly found oil

In the digital age, the phrase "data is the newly discovered oil" has become a mantra among technologists and business leaders alike. This analogy underscores the immense value of data in driving modern economies, much like oil did in the 20th century.

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The analogy of data as the newly found oil aptly captures its transformative potential in the digital age.

Data Engineer

Data engineering is a dynamic and rewarding field that sits at the intersection of technology and innovation. Whether you’re just starting out or looking to pivot in your career, the skills and knowledge you gain as a data engineer will open doors to endless opportunities.

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In the age of data, where information flows like a river and powers the engines of innovation.

Top 50 AIML Jargons

We have listed the most important 50 AIML jargons for you to read. There are many more, the listed ones are important as they cover a wide range of concepts, techniques, and tools essential to understanding and working in the field of AI and machine learning.

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Some of the most important one as they cover a wide range of concepts, techniques, and tools essential to understanding and working in the field of AI and machine learning.

Classifying AIML Algorithms

Machine learning algorithms can be categorized into several types based on their learning style and the type of problem they are designed to solve.

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Understanding types of machine learning algorithms helps in selecting the right approach for a given problem, optimizing model performance, and leveraging the strengths of each algorithm type.

Top 50 AIML Algorithms

Top 50 AI/ML algorithms involves a broad spectrum of techniques from various branches of AI and ML, including supervised learning, unsupervised learning, reinforcement learning, deep learning, and more.

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AIML algorithms encompass a wide array of methods used in AI and ML, each suitable for different types of problems and data characteristics.

Top 10 Programming Languages for AIML

The landscape of programming languages for Artificial Intelligence (AI) and Machine Learning (ML) is diverse, with each language offering unique strengths and capabilities.

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Programming languages offers unique benefits for AI and ML development, with choices often dependent on the specific requirements of the project, such as performance needs, ease of use, existing ecosystem, and integration capabilities.

Top 50 Python Libraries for AIML

Python libraries cover a wide range of tasks in AI and machine learning, from data manipulation and visualization to deep learning and reinforcement learning, making them essential tools for researchers and practitioners in the field.

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Python is one of the most popular languages for AI and ML due to its simplicity, readability, and extensive ecosystem of libraries.

10 weeks of Python

10 weeks of Python programming DIY concepts. Use the topic name and short description used to search for detailed explanation on GPT based bots, google and YouTube to observe, learn, practice and master the concepts.

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Top 50 Numpy Commands for Python

NumPy is the backbone of numerical computing in Python, a must-know for anyone diving into data science, machine learning, or scientific computing.

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50 essential NumPy commands that will supercharge your data manipulation and numerical computing skills. Whether you're a college student just starting out or a professional looking to enhance your toolkit, mastering these commands will set you up for success in your data science and machine learning endeavors.

Top 50 Pandas Commands for AIML

Welcome to the exciting world of Pandas, the go-to library for data manipulation and analysis in Python. Whether you're a college student dipping your toes into data science or a seasoned professional, these 50 essential Pandas commands will help you become a data wrangling wizard.

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A powerful toolkit of 50 Pandas commands at your fingertips.

XAI - Explainable AI

XAI stands for "Explainable AI", i.e. making AI models transparent to all. By making AI models transparent, we empower users and developers alike, ensuring that AI systems are not only smarter but also fairer and more accountable.

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Explainable AI (XAI) — the key to opening these black boxes and bringing clarity to the decision-making process of AI systems.

Hardware - Software Requirements for AIML

Hardware and software components are critical for different stages of AI development and deployment, including data preprocessing, model training, inference, and real-time processing. The choice of hardware depends on the specific requirements of the AI tasks and the desired balance between performance, cost, and flexibility.

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Developing AI and ML products requires a combination of hardware components, devices, configurations, and software tools.

Data Scientist

Data science is a thrilling field that combines curiosity, technical skills, and creative problem-solving. Whether you’re just starting or looking to shift gears in your career, the journey to becoming a data scientist is both challenging and rewarding.

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Unveiling the Mysteries of a Data Scientist: The Sherlock Holmes of the Digital Age

MLOps Engineer

MLOps engineers are the architects of AI, ensuring that the machine learning models built by data scientists are reliable, scalable, and integrated seamlessly into production systems.

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MLOps Engineer – the magicians behind the curtain who ensure that machine learning models are deployed, monitored, and maintained effectively.

Getting Started - MySQL

This article will enable you to install MySQL on windows OS, MacOS & Linux OS and perform CRUD operations.

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This article will enable you to install MySQL on windows OS, MacOS & Linux OS and perform CRUD operations.

PyTorch ~ TensorFlow ~ Keras

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In this series of blogs we will explore the foundations of Tensorflow, Keras and PyTorch

Introduction to PySpark

In this article, let's explore PySpark, a widely used library that serves as the interface for distributed data processing with Apache Spark

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PySpark is particularly used as a Python API to interact with apache spark which is a distributed data framework designed to handle large volumes of data

Introduction to Polars

Polars library is the latest entry in the world of data manipulation which works similar to Pandas with subtle differences In this article, let us focus on differences, performance and manipulation operations of polars library

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Polars is a data manipulation library similar to Pandas which is comparatively faster than pandas and it can handle large datasets

Feature Engineering

In this article, explore the world of feature engineering using automated libraries available exclusively for feature engineering task

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Feature engineering helps us to extract meaningful information (useful patterns ) from raw data which essentially improves the performance of machine learning models

100 Tools for Data Eng.

Checklist of 100 tools enabling data engineering pipelines on production environments

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DevOps ~ AIOps ~ MLOps

Comparing DevOps, MLOps, and AIOps: A short read for for College Students, Graduates, and Professionals. Let’s dive into an innovative and technical comparison that caters to college students, fresh graduates, and seasoned professionals.

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Git ~ GitHub ~ GitLab

Understand what Git, GitHub and GitLab does. Choose your champion tool based on your quest’s requirements. Whether you’re a lone coder, a collaborative team, or a DevOps powerhouse, there’s a tool ready to guide you on your path to digital mastery.

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Unlocking the Secrets of the Digital Repository: Git, GitHub, and GitLab

Unable to make to prod.

Artificial Intelligence and Machine Learning (AI/ML) are revolutionizing industries by offering unprecedented insights and automation. However, despite the buzz, a startling majority of AI/ML projects fail to make it to production. Understanding the reasons behind these failures can provide valuable lessons for aspiring data scientists, seasoned professionals, and businesses alike.

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AI/ML projects hold immense potential, but realizing this potential requires overcoming significant challenges.

Key AI Stakeholders

Key stakeholders for an AIML project encompass a broad range of roles, each contributing to the project's success from conception to deployment and beyond.

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Each stakeholder group plays a critical role in ensuring the AIML project meets its objectives, stays on budget, complies with regulations, and delivers value to users.

Involvement: Key to the Mastery

In the rapidly evolving landscape of education and professional development, this age-old wisdom from Benjamin Franklin resonates more than ever.

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" Tell me, and I forget. Teach me, and I may remember. Involve me, and I learn "

Agile

Welcome to the world of Agile Mythology—a realm where flexibility, collaboration, and continuous improvement guide the creation of groundbreaking technology.

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Explore all nooks and corners of the mysterious world of Agile methodology when it comes to having skills vs actually implementing them to one's use.

Claim it, know it, prove it!

In today's job market, there's a curious phenomenon unfolding. Picture this: a CV laden with grand achievements, cutting-edge projects, and skills that would make even the most seasoned professional nod in admiration. Yet, when the curtain rises and the interview spotlight shines, the illusion dissipates.

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Let your resume be a beacon of your real journey, not an illusion.