A naukri.com initiative
Data Science News
Medium
2w
424
Image Credit: Medium
5 Lessons I’ve Learned As An Engineering Manager
- Transitioning from engineer to engineering manager comes with challenges and lessons.
- Building a strong team requires finding and retaining dependable people with shared values.
- Understanding that code is predictable, but people's behaviors and motivations are not, is crucial in management.
- Effective leadership involves supporting individuals rather than trying to control them.
- Learning to navigate uncomfortable situations and address conflicts is essential for managerial growth.
- Leading without certainty means making decisions without perfect options and embracing the outcome.
- Prioritizing values over immediate gains leads to long-term success and sustains company culture.
- Successful leadership is about making decisions, moving forward, and earning your team's trust.
- Working in line with personal and organizational values creates meaningful outcomes beyond financial gain.
- Being an engineering manager is challenging yet rewarding, offering opportunities for growth and innovation.
Read Full Article
25 Likes
Medium
2w
320
Image Credit: Medium
You will never be a killer PM in a Corporate Setting
- After excelling in analytics, Amy decided to transition to a product management role.
- However, she quickly realized that in many corporate settings, the role of a product manager is often limited to mundane tasks like creating playbooks and taking notes in meetings.
- Amy grappled with the shallowness of her role and sought ways to grow beyond the constraints of the corporate environment.
- The article suggests three paths for Amy's development as a true product manager: building something on her own, becoming an intrapreneur within the organization, and being a lifelong student through mentorship and hands-on learning.
- It emphasizes the importance of hands-on experience, data-driven decision-making, and the ability to balance hard and soft skills in product management.
Read Full Article
19 Likes
Analyticsindiamag
2w
142
Image Credit: Analyticsindiamag
Vibe Coder Gets Legal Notice From DocuSign
- DocuSign sent a legal notice to Michael Luo, a developer who created a free e-sign tool similar to its services using platforms like ChatGPT, Cursor, and Lovable.
- DocuSign accused Luo of disseminating false information about their product and copying their intellectual property.
- Luo denies stealing or making misleading statements and claims DocuSign felt threatened by his free tool.
- Despite the legal notice, Luo is continuing to enhance his free e-sign tool named Inkless.
- DocuSign allows free document signing but limits signature collection to three documents with a free account.
- Using AI to develop applications, known as 'vibe coding', has seen rapid growth in recent months as per Andrej Karpathy.
- Developers using AI encounter legal concerns like receiving notices from companies like DocuSign.
Read Full Article
8 Likes
Medium
2w
385
Image Credit: Medium
How to Deploy Small Scale LLMs on a Budget
- Deploying Small Scale LLMs on a Budget: What Hardware and Software Do You Really Need?
- Running small scale large language models (LLMs) efficiently with modest resources is possible with the right approach.
- Balancing power and cost is crucial when setting up small scale LLMs on a budget.
- You can achieve good results with smaller GPUs and a suitable software stack instead of high-end options like the Nvidia A100.
- Optimizing hardware and software choices can lead to significant cost savings in deploying LLMs.
- Understanding the essential hardware and software requirements is key to running small scale LLMs smoothly and economically.
- Finding the right balance between performance and affordability is the main challenge in deploying LLMs on a budget.
- Efficient deployment of small scale LLMs involves choosing the right mix of hardware and software components.
- Prioritizing the necessary components while avoiding unnecessary expenses is crucial for budget-friendly deployment of LLMs.
Read Full Article
23 Likes
Medium
2w
386
Image Credit: Medium
Interstellar Travel: The Astrophysical Reality of Warp Drives and Wormholes
- Humanity has always looked to the stars for destiny, but remains light-years away from habitable exoplanets.
- The astrophysical discourse on Warp Drives and Wormholes explores mathematical possibilities within General Relativity, Quantum Field Theory, and Topological Engineering.
- Einstein's Speed Limit from Special Relativity restricts objects with mass from reaching the speed of light, but concepts like warp drives aim to manipulate space around us.
- Wormholes and warp drives face theoretical and practical challenges, requiring exotic matter and energy levels beyond current capabilities.
- Theoretical models suggest wormholes exist at the Planck scale, posing challenges for enlargement and energy requirements.
- Manipulating spacetime for interstellar travel raises concerns about time travel and spacetime distortions, challenging known physics principles.
- No observational data confirms the existence of traversable wormholes or warp-like geometries, hindering progress towards engineering goals.
- Active research areas include post-classical propulsion physics, experimental spacetime modeling, and cross-disciplinary collaboration.
- While warp drives and wormholes remain speculative, they are mathematically possible within current physics frameworks.
- Innovative theoretical thinking, collaboration, and a vision for the future can pave the way for interstellar travel possibilities.
- The journey towards interstellar travel requires bending rules and embracing theoretical innovation for potential future advancements.
Read Full Article
23 Likes
Medium
2w
186
Image Credit: Medium
The Preprocessing Survival Guide for New Data Scientists
- New data scientists often face challenges with real-world messy data compared to clean, toy datasets used in training.
- Understanding the true context of missing values is crucial for accurate preprocessing.
- Imputing nulls with zeros in specific cases is more meaningful than using means or medians.
- Choosing between mean and median imputation depends on data distribution, favoring median for skewed data.
- Category-wise null imputation can provide more accurate results than overall imputation.
- Drop_duplicates function may overlook subtle differences and requires thoughtful parameter selection.
- Scaling data using StandardScaler or MinMaxScaler is essential for models sensitive to feature magnitudes.
- Feature engineering helps control the explosion of columns in categorical data, improving model performance and explainability.
- Utilizing feature decomposition algorithms like PCA can manage excessive one-hot encoded columns effectively.
- Careful consideration is needed when removing outliers to avoid discarding valuable insights within the data.
Read Full Article
11 Likes
Medium
2w
238
Image Credit: Medium
Discover How I Earned $500 in Just One Week!
- The article discusses the author's experience of earning $500 within a week using an innovative earning platform.
- The platform provided genuine value and opportunities to earn a consistent income online.
- The author found the platform easy to navigate and was able to connect with others leveraging the platform.
- Consistency and community were highlighted as key aspects that contributed to the author's success.
- The author shared insights and strategies with others on the platform to boost earnings.
- Success stories from other users, like Jane, who made $2,000 in her first month, were mentioned.
- The comprehensive training videos and resources on the platform helped users thrive.
- Adaptability and making adjustments based on community feedback were crucial for success.
- The author's mindset and income saw significant changes within a couple of months.
- The article encourages readers to explore the earning platform to achieve financial goals.
- Starting today and engaging with users on the platform is recommended for success.
- The platform offers the potential to make extra income, from a few hundred dollars to boosting financial freedom.
- The article emphasizes the simple changes in strategy that can yield extraordinary results.
- The author's success story showcases how dedicated effort and networking led to financial gains.
- The practical features of the platform enabled quick adaptation and results for the author.
- The platform helped users, like the author and Jane, transform their finances through consistent work and utilizing resources.
Read Full Article
14 Likes
Medium
2w
390
From Backlogs to Algorithms: My Journey into AI/ML From Rock Bottom
- The author shares their journey from struggling academically to aspiring to become a Machine Learning Engineer.
- Despite early setbacks like low grades, backlogs, and doubts, the author is determined to succeed in the field of AI/ML.
- The story emphasizes slow and steady progress and is meant to inspire students who feel they have already failed.
- The author discovered AI/ML as a field that values hard work and learning potential over past academic performance.
- Universities and companies are increasingly valuing skills, projects, and determination over traditional metrics like grades.
- The author has a two-year plan to showcase their skills and earn a place in a top university for AI/ML.
- The message encourages readers to start small, be consistent, learn daily, and focus on skill-building and progress.
- The narrative underscores the importance of perseverance, learning from failures, and continuous improvement.
- The author's journey is portrayed as an ongoing process with the potential for future success and growth.
- The article serves as a motivation for individuals pursuing goals in AI/ML and emphasizes the journey rather than just the outcome.
- The author hopes that one day they will be able to share their own success story as someone who overcame obstacles in their educational journey.
Read Full Article
23 Likes
Medium
2w
495
Image Credit: Medium
"How Artificial Intelligence is Transforming Our Daily Lives" ✨
- AI powers self-driving cars, real-time traffic updates, and ride-sharing apps like Uber and Careem.
- Voice assistants like Siri, Alexa, and Google Assistant help with various tasks hands-free.
- AI saves lives by aiding doctors in quicker disease detection, assisting in surgeries, and managing patient records.
- AI enables fitness apps and smartwatches to track health and provides personalized health insights.
- AI understands user preferences, suggesting personalized suggestions on platforms like Amazon and Netflix.
- For businesses, AI helps with chatbots, automated emails, and targeted advertising based on customer behavior.
- AI-powered learning platforms offer personalized content for students like Duolingo and Khan Academy.
- The role of AI is to enhance human life in various aspects, from home to hospital, school to the office.
Read Full Article
17 Likes
Medium
2w
368
Image Credit: Medium
Mastering the Machine Learning Workflow - A Practical Guide for Supervised Learning
- The workflow for machine learning involves several steps to ensure the usage of updated data including understanding the need for machine learning and conducting thorough research in the relevant business field.
- Collecting data from various sources and exploring it in tools like Excel or programming languages like Python are crucial initial steps.
- Data preprocessing steps such as handling null values, dealing with imbalanced data, removing duplicate rows, and fixing inconsistencies are necessary for preparing the dataset.
- Exploratory Data Analysis (EDA) helps in identifying patterns, errors, and relationships among variables through visualization techniques.
- Feature engineering involves tasks like train-test splitting, encoding categorical features, and creating new features if required.
- Careful consideration is needed for encoding before train-test splitting to avoid data leakage and ensure model performance on new unseen data.
- Feature selection methods like variance threshold, correlation coefficient, and tree-based feature importance help in selecting relevant features for model training.
- Hyperparameter tuning and evaluating metrics like Regression and Classification are crucial for selecting the best model for the dataset.
- Once the best fitting algorithm is determined, hyperparameters are optimized, and the model trained, it is saved in a serialized object format like .pkl for future use.
- Deploying the saved model for real-time inference can be done by creating an API, commonly using Flask API, and updating the model periodically with changing data is essential for maintaining performance.
- This comprehensive guide provides actionable insights into leveraging machine learning for data-driven decisions, emphasizing the importance of continuous learning and improvement in the field.
Read Full Article
22 Likes
Dev
2w
134
Image Credit: Dev
Fine-Tuning a Language Model for Summarisation using LoRA
- Summarisation involves extracting important points from a large body of text, done through either extractive or abstractive methods.
- Extractive summarisation treats each sentence as a binary classification problem, simplifying the summarisation process but with limited capabilities.
- Abstractive summarisation generates a new paragraph based on the meaning of the original text, more expressive yet complex to implement.
- Fine-tuning a small T5 variant using LoRA, a technique updating low-rank matrices, effectively balances model performance and efficiency.
- LoRA is ideal for efficient training in low-resource environments and multiple models, reducing parameter updates while maintaining expressivity.
- Utilizing Hugging Face, the project fine-tunes the model using LoRA, emphasizing fast prototyping and adaptable pipeline for real-world tasks.
- BERTScore F1 metric was employed to evaluate summarisation performance, showcasing improvement through LoRA fine-tuning in comparison to the vanilla model.
- While the project showcases adapter-based fine-tuning, concerns include domain transfer testing, training duration, inference optimization, and token limits for efficiency.
- Despite limitations, the project demonstrates the effectiveness of minimal fine-tuning updates on a pretrained model to enhance performance.
- The project serves as a learning experience in implementing adapter-based fine-tuning with LoRA and welcomes input on improving evaluation metrics and techniques.
Read Full Article
8 Likes
Medium
2w
347
Image Credit: Medium
Hyper-Realistic AI Avatars
- Hyper-realistic AI avatars are revolutionizing digital connections, communications, and collaborations.
- Advances in technology have enabled the creation of avatars that closely resemble real individuals.
- Machine learning, computer vision, and voice synthesis contribute to the lifelike features of these avatars.
- Hyper-realistic avatars can replicate facial expressions, preserve unique voices, and convey emotions realistically.
- These avatars are no longer mere novelties but are crucial tools in healthcare, education, customer service, and other sectors.
- A breakthrough by the Electronics and Telecommunications Research Institute allows creating lifelike avatars from a single photograph.
- This technology enhances accessibility for various individuals, including those with disabilities.
Read Full Article
20 Likes
Medium
2w
209
Image Credit: Medium
Demystifying AI: What Is Artificial Intelligence and Where It’s Headed in 2025
- AI, or Artificial Intelligence, involves teaching machines to think, learn, and make decisions like humans.
- AI has evolved from science lab demos to everyday applications thanks to advanced algorithms, cloud computing, and vast amounts of data.
- Python is a preferred language for AI development due to its simplicity and extensive library support.
- Future AI will encompass vision, language understanding, and actions, enhancing real-time capabilities on various devices.
- AI will enable goal-driven digital agents, eliminate the need for coding, and introduce generative capabilities like writing and designing.
- AI is making significant impacts in various fields such as healthcare, education, finance, transportation, and entertainment.
- It is crucial to ensure AI is used ethically, transparently, and for the benefit of all individuals.
- Understanding AI does not require an engineering background, as it primarily involves math, data, and creativity.
- The current era offers an ideal opportunity for individuals to start learning about AI and its vast possibilities.
Read Full Article
12 Likes
Dev
2w
65
Image Credit: Dev
A Beginner’s Note on Natural Language Processing: Key Takeaways
- Natural Language Processing (NLP) is a crucial branch of Artificial Intelligence that enables machines to understand and respond to human language.
- NLP combines computer science, linguistics, and deep learning techniques to process language intelligently, allowing for translation, summarization, question answering, and more.
- NLP is essential as it deals with unstructured data like text and speech, enabling computers to read, understand meaning, and generate responses.
- Key components of NLP include text preprocessing, linguistic rules, and deep learning models like RNNs, LSTMs, Transformers, and models such as GPT.
- Popular tools in NLP include libraries like spaCy, NLTK, Hugging Face Transformers, and services like OpenAI API for leveraging deep learning models.
- Applications of NLP span text classification, chatbots, text summarization, question answering, speech recognition, text generation, grammar checking, and named entity recognition.
- NLP is instrumental in various fields like customer service, education, content creation, and grammar correction, enhancing user experiences and simplifying tasks.
- Understanding NLP is valuable for developers building text-interacting applications, making them smarter, more helpful, and user-centric.
- NLP lies within the broader scope of Artificial Intelligence, Machine Learning (ML), and Deep Learning (DL), focusing specifically on language understanding.
- Learning NLP empowers developers to create intelligent, human-centric applications like chatbots, voice assistants, and translation tools, leading to enhanced user engagement.
Read Full Article
3 Likes
Medium
2w
47
# Why Everyone Should Understand the Basics of Data in 2025
- Data is ubiquitous, with individuals generating significant amounts daily through various activities like reading, watching videos, leaving likes, taking routes, and making purchases, all of which are collected and analyzed for or against them.
- Understanding data basics grants individuals the ability to make informed decisions, ask better questions, identify bias, interpret data accurately, and enhance testing and improvement processes.
- Three essential data skills to master include Excel or Google Sheets for basic data handling, data visualization tools like Tableau and Power BI for creating visual stories, and analytical thinking to question data reliability and interpretation.
- One does not require a tech background to delve into data analysis, as learning through tutorials, courses, and practical applications like Excel can pave the way to becoming adept in utilizing data for personal and professional growth.
- In today's data-driven world, those capable of interpreting and utilizing data effectively take the lead, while others lag behind, emphasizing the importance of engaging with data to stay ahead in various aspects of life.
Read Full Article
2 Likes
For uninterrupted reading, download the app