The concept of Machine Learning, Artificial Intelligence (AI), Big Data has been around for a while. But the ability to apply algorithms and mathematical calculations to big data is gathering momentum only recently.
In this article we will discuss the importance of Machine Learning and why every Data Scientist must master it.
What is Machine Learning?
Simply put, we’re contributing to Machine Learning through our day to day interactions on the internet. Whether you search your coffee maker on Amazon, “top tips to lose weight” In Google, or “friends” in Facebook you see Machine Learning in action, but you don’t realize it.
It is the Machine Learning technology that lets Google, Amazon, and Facebook search engine offer relevant recommendations to the user.
These companies are able to keep tabs on your day to day activity, search behavior and shopping preference with the help of ML technology.
Machine Learning is also one of the main components of Artificial Intelligence.
Who is a Data Scientist?
Before assessing the importance of Machine Learning for Data Scientists, here’s a brief note on who Data Scientists are. We’ll also discuss how one can become a Data Scientist.
Data Scientists draw meaningful information from a huge volume of data. They identify patterns and help build tools like AI-powered chatbots, CRMs, etc. to automate certain processes in a company.
With a sound knowledge of different Machine Learning techniques and contemporary technologies like Python, SAS, R, and SQL/NoSQL database, Data Scientists perform in-depth statistical analysis.
The role of Data Scientist might sound like that of Data Analyst, but, in fact, they are different.
Difference between a Data Scientist and a Data Analyst
Data scientist predicts future based on past patterns. Whereas, a Data Analyst curates meaningful insights from data.
Data scientist’s work involves “estimation” (or prediction) unknown facts; while an analyst investigates the known facts.
Data Analyst’s job is more geared towards businesses. Data Scientists’ work is integral to innovations and technological advances.
Why Machine Learning is So Important for a Data Scientist?
In a near future, process automation will superimpose most of the human-work in manufacturing. To match human capabilities, devices need to be intelligent and Machine Learning is at the core of AI.
Data Scientists must understand Machine Learning for quality predictions and estimations. This can help machines to take right decisions and smarter actions in real time with zero human intervention.
Machine Learning is transforming how data mining and interpretation work. It has replaced traditional statistical techniques with the more accurate automatic sets of generic methods.
Hence it is imperative for Data Scientists to acquire skills at Machine Learning.
4 Must Have Skills Required to Become a Machine Learning Expert
To become an expert at Machine Learning every Data Scientists must have the following 4 skills.
Thorough knowledge and expertise in computer fundamentals. For example, computer organization, system architecture and layers, and application software.
Knowledge of probability is very important because Data Scientists’ work involves a lot of estimation. Analyzing statistics is another area that they need to focus on.
Data modeling for analyzing various data objects and how they interact with each other.
Programming skills and a sound knowledge of programming languages like python and R. A quest for learning new database languages like NoSQL apart from traditional SQL and Oracle.
Conclusion
Data is the new oil.
IBM predicts that the global demand for Data Scientists will rise 28% by 2020. Finance, Insurance, Professional services and IT sectors will cover 59% of the Data Science and Analytics job demand.
In the coming future, Machine Learning is going to be one of the best solutions to analyze high volumes of data. Therefore, Data Scientists must acquire an in-depth knowledge of Machine Learning to boost their productivity.
This article is contributed to Mantra Labs by Jenny Hayat. Jenny is an established blogger and content writer for business, career, education, investment, money-making ideas and more.
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Design Systems: Building and Maintaining Consistent UI/UX
In the world of product design, consistency is the cornerstone of delivering a seamless user experience. As digital products evolve and scale, the challenge of maintaining design consistency across multiple platforms, teams, and touchpoints becomes more complex. This is where design systems come in. A design system is a comprehensive set of guidelines, components, and tools that help designers and developers create a consistent and cohesive user interface (UI) and user experience (UX). From a designer’s perspective, building and maintaining a design system requires a strategic approach to ensure scalability, flexibility, and alignment with business goals.
Design systems are more than just style guides or pattern libraries. They offer a unified language for design and development, bridging the gap between creativity and functionality. Here are a few reasons why they are critical:
Consistency Across Products
One of the primary goals of a design system is to ensure uniformity across different platforms and devices. When users interact with a product, whether on a website or a mobile app, they expect a consistent experience. A well-implemented design system ensures that visual elements, interactions, and behaviors are aligned, offering a familiar and intuitive experience for users.
2. Faster Iteration
With a design system in place, teams can reuse components and patterns rather than reinventing the wheel for each new feature. This speeds up the design and development process, allowing teams to focus on solving new problems instead of reworking existing designs. For designers, it means less time spent on repetitive tasks and more time dedicated to innovation.
3. Scalability
As products grow and new features are added, maintaining a coherent UI/UX without a design system can become chaotic. A design system provides a scalable framework, enabling teams to add new elements or modules without compromising the overall consistency of the product.
4. Improved Collaboration
A design system fosters collaboration between designers, developers, and other stakeholders by providing a shared language and reference point. This ensures that design decisions are communicated effectively, reducing friction and misunderstandings between teams.
Building a Design System: A Designer’s Perspective
Designing a system from scratch can seem like a daunting task, but with a clear roadmap and understanding of core principles, it becomes a powerful tool for creating scalable and user-centered products.
1. Define the Core Principles
Before diving into visual components, it’s essential to establish the core principles of your design system. These principles serve as the foundation and guide decision-making throughout the process. Ask yourself:
• What are the key values of your brand?
• How should the design reflect the needs and emotions of users?
• What goals are you trying to achieve with your design system (e.g., accessibility, flexibility, innovation)?
For instance, if accessibility is a top priority, you’ll need to ensure that your design system accommodates users with different abilities, by providing color contrast guidelines, clear typographic hierarchies, and accessible components.
2. Create a Unified Visual Language
Once the principles are established, the next step is creating a cohesive visual language. This includes defining elements such as:
• Color Palette: A well-structured color palette ensures harmony across different UI components. It’s crucial to include primary, secondary, and accent colors, along with usage guidelines to avoid inconsistency.
• Typography: Define a typography system that establishes hierarchies and clarity, including font styles, sizes, line heights, and spacing. Consistent typography helps users navigate content effortlessly.
• Spacing and Grids: An established grid system ensures a balanced layout and harmony between different UI elements. Proper spacing guidelines prevent crowded or misaligned components.
• Iconography and Illustrations: Design guidelines for icons and illustrations help maintain visual consistency. Icons should follow a standard style (outlined, filled) and size, ensuring they align with the overall visual language.
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Iconography and Illustrations: Design guidelines for icons and illustrations help maintain visual consistency. Icons should follow a standard style (outlined, filled) and size, ensuring they align with the overall visual language.
A design system is incomplete without reusable UI components. These components include buttons, forms, modals, and navigation elements that can be used across various features and pages. Each component should be:
• Modular: Components should be flexible and adaptable for different contexts. For example, a button should have variations for different states (hover, active, disabled) and types (primary, secondary, destructive).
• Documented: Each component needs comprehensive documentation that explains how it should be used, its variants, and the rules governing its application. This ensures consistency when different team members use the same component.
4. Implement Accessibility Guidelines
Accessibility should be at the forefront of every design system. As a designer, consider:
• Color Contrast: Ensure sufficient contrast between text and background for readability.
• Keyboard Navigation: Ensure that interactive components are navigable via keyboard for users who rely on keyboard shortcuts.
• Responsive Design: Components should be responsive, adapting seamlessly across different screen sizes and devices.
• Assistive Technologies: Design components should be compatible with screen readers and other assistive technologies to provide an inclusive experience.
Maintaining a Design System: Evolving with the Product
Once a design system is in place, the work doesn’t stop there. Maintaining it requires ongoing effort as the product evolves and new design challenges emerge. Here’s how designers can ensure the design system remains relevant and effective:
1. Regular Audits and Updates
A design system should be treated as a living document that evolves with the product. Regular audits are necessary to identify outdated or unused components. Designers should collaborate with developers to ensure new features are aligned with the existing design system, and updates should be documented to avoid fragmentation.
2. Version Control and Documentation
Version control is essential for keeping track of changes in the design system. Documenting why and how changes are made ensures that the design system grows in an organized manner. It also helps onboard new team members quickly, as they can reference updated guidelines.
3. Foster Collaboration Across Teams
Designers need to maintain an open line of communication with developers and other teams using the design system. Tools like Figma, Sketch, and Zeplin allow designers to share components and guidelines in real-time, fostering collaboration and ensuring that everyone is aligned.
Some well-known examples of design systems that have set benchmarks in the industry:
Overview: Google’s Material Design is one of the most comprehensive design systems available. It provides guidelines on how to create visual, motion, and interaction design across platforms and devices. Material Design is known for its grid-based layouts, responsive animations, and depth effects like shadows and lighting.
Features:
Comprehensive color palettes, typography, and iconography.
Overview: Salesforce’s Lightning Design System provides a comprehensive library of UI components and resources to help build applications on the Salesforce platform. It ensures a consistent experience across Salesforce products and enables developers to create custom apps easily.
Features:
Ready-to-use components, design tokens, and code snippets.
Comprehensive accessibility guidelines to ensure inclusivity.
Detailed documentation for developers to integrate components into Salesforce applications.
Overview: Fluent Design is Microsoft’s design system, created to provide an engaging and scalable UI across all Microsoft products. It is heavily focused on interaction, animation, and motion while ensuring accessibility across various device ecosystems.
Features:
Focus on depth, motion, and light to create modern and interactive UIs.
Cross-platform components supporting web, desktop, and mobile applications.
Accessible components with detailed guidelines for developers.
Conclusion
Building and maintaining a design system is an investment that pays off in the long run. It ensures consistency across your product, improves collaboration between teams, and allows for faster iteration and scalability. For designers, a design system is more than a collection of reusable components — it’s a framework that enables you to create user-centric products with confidence and clarity. By embracing modularity, documentation, and accessibility, you’ll ensure that your design system remains a valuable asset as your product grows.
About the Author:
Shristi is a creative professional with a passion for visual storytelling. She recently transitioned from the world of video and motion graphics to the exciting field of product design at Mantra Labs. When she’s not designing, she enjoys watching movies, traveling, and sharing her experiences through vlogs.
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