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Educba
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Cloud Salon Software
- Cloud salon software is a digital platform hosted on remote servers. It enables businesses to access their data and functionalities over the Internet. Cloud-based solutions eliminate the need for expensive hardware and complex installations comparing to traditional on-premises systems. Remote accessibility to data, automated scheduling appointments, real-time update facilities, personalized marketing campaigns contributing to increased customer satisfaction, scalability, cost-effectiveness, and real-time data insights are some advantages of cloud salon software.
- Robust, scalable, and user-friendly systems have driven the adoption of cloud-based software. Research predictions suggest that the clients will book 78 percent of salon appointments online by 2025, highlighting the growing need for digitized operations.
- Cloud software automates manual processes like appointment scheduling, inventory tracking, and customer follow-ups that improve operational efficiency. Automated reminders reduce no-shows, directly boosting revenue.
- Personalized marketing campaigns based on customer preferences and simplified booking and payment processes enhance customer experience.
- Cloud-based systems can scale to meet business needs, whether businesses run a single salon or a chain of massage parlors. There is no need for costly hardware or IT maintenance and instead uses flexible pricing models that grow with businesses.
- Real-time data insights into businesses' performances with analytics and reporting tools offered by cloud-based software.
- Companies like Dermani Medspa, Sono Bello, and Zenoti's Salon Name Generator and Tip Calculator have shown the successful implementation of cloud-based software, improving operations, driving efficiency, and improving customer experiences.
- Common challenges in implementing cloud-based software include resistance to change from staff, initial learning curve with new systems and data security concerns. Effective solutions to these challenges include training staff, choosing providers with robust data encryption and compliance certifications, and starting with a phased implementation.
- Wider accessibility to affordable cloud-based tools, the ability to drive standardized practices in appointment booking, payment processing, and customer management across the industry, and further integration with AI, IoT, and AR are the future outlook for cloud-based software.
- Cloud-based salon software eliminates the need for expensive hardware and complex installations, and offers various advantages that help salons improve efficiency, enhance customer experience and optimize overall business performance. Adopting cloud-based salon software can future-proof businesses and ensure a competitive edge in this evolving industry.
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HRKatha
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CARS24 to Hire 100+ tech experts by March 2025
- Indian autotech platform CARS24 plans to hire at least 100 technical experts over the next four months.
- The company will invest Rs 500 crores in advancing its technology and product ecosystem.
- The tech experts will be hired for roles in data science, genAI, machine learning, devops, and product innovation.
- CARS24 aims to make car ownership smarter and better through its Super App, offering features like real-time car valuations, maintenance tracking, and more.
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Analyticsindiamag
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India is the Land of Weekend AI Engineers
- India has the highest AI skill penetration rate globally with a projected AI talent pool growth of 1.25 million by 2027.
- There are concerns about the quality and depth of AI talent in India, with many professionals being labeled as 'weekend engineers' who lack fundamental knowledge.
- The focus in India has been on applied engineering rather than research engineering, leading to a lack of understanding behind AI principles.
- India is known for being a service provider in the software ecosystem, and its contribution to core R&D in AI is considered negligible compared to countries like China.
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Jetbrains
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The State of Data Science 2024: 6 Key Data Science Trends
- The latest iteration of the Python Developer Survey, collected between November 2023 and February 2024, includes a new Data Science section which allowed for a more complete picture of trends over the past year.
- Data processing is an essential part of data science and pandas is still at the top of most commonly used data processing tools, used by 77% of respondents.
- Polars is gaining ground and been in the spotlight due to the advantages it provides in terms of speed and parallel processing, with 10% of respondents reportedly using the tool.
- Plotly Dash was the most popular visualization dashboard tool, however, HoloViz Panel is gaining traction within the PyData community and could catch up within the next year.
- Scikit-LMM is a new library worth paying attention to that allows you to tap into Open AI models to perform text analysis.
- MLOps tools designed for data science projects have emerged and continue to progress with tools like Docker containers now slightly ahead of Anaconda in the Python installation and upgrade category.
- Big data requires distributed computing resources such as Apache Spark and PySpark for better performance and scalability.
- Python events like PyCon and EuroPython have shifted focus towards data science with more tracks, talks, and workshops catering to data science use cases.
- The latest developments in the fields of data science and machine learning continue to rapidly change.
- PyCharm is an integrated development environment that can help data scientists efficiently build their skill set, providing intelligent coding assistance, top-tier debugging, version control, integrated database management, and seamless Docker integration.
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Dev
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From Data to Decisions: Understanding Machine Learning Algorithms💻
- Machine learning is a subset of artificial intelligence (AI) that focuses on building systems that can learn from data.
- Machine learning algorithms analyze patterns in data to make predictions or decisions.
- Machine learning algorithms follow these steps: Data Collection, Data Preparation, Choosing an Algorithm, Training the Model, Testing the Model, Making Predictions.
- In supervised learning, algorithms are trained using labeled data.
- Unsupervised learning algorithms work with unlabeled data. The goal is to find hidden patterns or groupings within the data.
- Reinforcement learning involves training algorithms through trial and error by interacting with an environment.
- Selecting the right machine learning algorithm depends on several factors.
- Machine learning algorithms are used in various industries for numerous applications: Healthcare, Finance, Marketing and Transportation.
- Machine learning plays a crucial role in transforming raw data into meaningful insights that drive decision-making.
- Experimenting with different algorithms on real datasets will deepen your understanding and help you become proficient in this exciting field!
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Medium
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From Code to Leading MLOps practice: My MLOps Journey & Insights
- Eliot Amal J shares his MLOps journey and insights.
- Started with creativity and a hackathon, Eliot transitioned from full-stack development to MLOps.
- Scaled MLOps practice by addressing gaps in documentation, architecture artifacts, MLOps operating model, impactful demos, and building bridges with ML platform providers and thought leaders.
- MLOps is considered as the future of AI, bridging the gap between innovation and implementation.
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Medium
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Crossroads of Innovation: AI’s Role in Interdisciplinary Evolution, Transforming Business and…
- AI’s interdisciplinary edge lies in its ability to integrate methodologies from diverse fields, creating powerful solutions that are greater than the sum of their parts.
- AI is revolutionizing business operations by enabling smarter, faster decisions and creating new opportunities.
- The adoption of generative AI is poised to significantly impact various industries and job markets, including manufacturing, healthcare, retail, transportation, and finance .
- Generative AI (Gen AI) is set to drive significant economic changes, primarily by boosting productivity through efficiency gains and accelerating innovation.
- However, the labor market faces challenges, including job losses in sectors where automation replaces human workers and downward wage pressures in roles that AI can perform.
- As AI continues to integrate across disciplines, it presents both opportunities and challenges.
- The diverse data sources used in interdisciplinary AI applications can amplify biases if not handled carefully, and sensitive data requires strong protections.
- Moreover, ensuring that the benefits of AI reach underserved communities remains a critical challenge.
- Looking ahead, AI’s interdisciplinary role is set to grow, with emerging fields like quantum computing and synthetic biology benefiting from AI’s capabilities.
- The future of AI holds immense promise, and our collective responsibility lies in ensuring its benefits are shared by all.
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Analyticsindiamag
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Floworks Launches New Tool Use Feature in Alisha 3
- YC-backed Indian startup Floworks has launched a new feature called ‘Tool Use’ in their AI sales development representative, Alisha.
- The feature allows customers to build custom workflows using natural language and integrate major sales tools.
- Alisha can fetch data from third-party tools like Gmail, Salesforce, and HubSpot.
- Floworks aims to strengthen the outreach layer and enhance engagement with personalized emails and communication.
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Medium
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Understanding Synthetic Data: Applications and Use Cases in the Modern Era
- Synthetic data refers to artificially generated information that mimics the statistical properties of real-world data.
- It is used in various applications such as data augmentation, bias mitigation, simulation-based training, privacy preservation, medical imaging, fraud detection, risk analysis, personalization, and demand forecasting.
- Specific use cases of synthetic data include autonomous vehicles, anti-fraud models in finance, medical AI models, e-commerce recommendation systems, and digital twins in manufacturing.
- Despite its benefits, synthetic data poses challenges in terms of accuracy, validation, and ethical considerations.
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Analyticsindiamag
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The Human in the Loop Is the Real Problem
- Large language models (LLMs) reflect the biases of their creators, warns a new study. This bias is true for models from OpenAI, Alibaba, Google, Anthropic. A dataset of over 4,000 controversial political figures was derived from Wikipedia and used to perform tests on seventeen AI models, both Western and non-Western . Non-Western models showed a preference for centralised governance, law enforcement and cultural values, and were more positive about political persons critical of liberalism, human rights, and minority groups.
- AI sceptics who claim that there will always be a human in the loop need to consider new research sparking fresh concerns about AI models and what AI scholars call LLMs. There is concern that LLMs reflect the ideological biases of their creators.
- The study shortlisted over 4,000 controversial, historical political figures Whitney summaries were available on Wikipedia. The dataset, derived from Wikipedia, carries a bias due to the platform's open-edit nature. Additionally, ideologies and societal norms evolve over time, and anything considered conventional in the past might be considered uncommon today.
- Both Western and non-Western models rated figures tagged with their ideologies and associated with their country positively. English-prompted LLMs exhibited a pro-liberal outlook while the Chinese-prompted models were favourable towards state-led economic policies.
- Chinese AI models have shaken the AI ecosystem in the past few weeks. The new DeepSeek AI challenges the reasoning capabilities of OpenAI’s o1, which is yet to release. Alibaba Qwen 2.5 Coder demonstrated strong coding capabilities, even better than Anthropic’s Claude in some cases. All of these models are open source.
- The paper’s findings can be attributed to Conway’s law that states, “organisations which design systems are constrained to produce designs that are copies of the communication structures of these organisations”.
- Dealing with bias in traditional and social media apps is not a new problem, but consumers may have to make a conscious choice in the future based on the creator of the model.
- AI models reflect the biases of their creators according to a new report. Bias is present in the datasets on which models are trained, as well as in the design of their creator organisations.
- Nonetheless, the paper’s findings can be attributed to Conway’s law and the nature of AI models in general.
- AI researcher Paras Chopra predicts that AI bias is a problem that will never be solved. Rather, users will have to make choices based on their preferred bias.
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Medium
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Smallest Number in an Array Python
- To find the smallest number in an array in Python, you can use the sorting method or write a custom algorithm.
- One approach is to sort the array and the smallest number will be at the first position.
- Another approach is to use a custom algorithm, where you assume the first element as the smallest number and iterate through the array to find any smaller numbers.
- The algorithm involves starting from index 1 and comparing each element to the current smallest number.
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Analyticsindiamag
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120
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Oracle Quietly Becomes Every Cloud’s Best Friend
- Oracle has entered the multi-cloud era with partnerships with Microsoft Azure, Google Cloud, and AWS.
- Oracle's strategy is based on its control over data and being more open than its counterparts.
- Major companies like Vodafone and Voya Financial are using Oracle's multi-cloud services.
- Oracle's cloud services revenue grew in Q1 2025, but it still lags behind competitors AWS, Microsoft Azure, and Google Cloud.
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Analyticsindiamag
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Bengaluru Emerges as the Hotspot for GCCs
- Canadian information management giant OpenText expands its Bengaluru-based centre of excellence (CoE) in India.
- The Bengaluru CoE houses engineering and product development teams focused on OpenText's business clouds, AI, cybersecurity, and DevOps.
- Bengaluru has seen a 194% increase in OpenText's workforce in the last two years, contributing to 25% of the company's global workforce.
- Bengaluru has emerged as a hotspot for Global Capability Centers (GCCs) in India, attracting global companies with its strong IT industry, skilled workforce, and good infrastructure.
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Analyticsindiamag
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423
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What’s Nutanix Cooking Up for New Bharat?
- At the Nutanix .NEXT India tour event, the cloud software giant elaborated on its role in transforming India into a ‘new Bharat’.
- The company is fueling innovations in sectors as diverse as banking, automotive, oil and gas, pharmaceuticals, IT/ITeS, and software.
- Nutanix powers government state data centres, strengthens hospitals, and fortifies the Indian defence forces.
- Historically known for virtual machine management, Nutanix has shifted focus toward containerisation.
- Nutanix integrates seamlessly with partners like NVIDIA for AI processing and offers robust data services.
- Nutanix has an ecosystem-driven approach, collaborating with major players such as AWS, AMD, and HPE.
- Nutanix’s exclusive channel model involves working closely with Indian resellers and managed service providers.
- One of the clients Nutanix is working to help in automating financial services is HighRadius.
- HighRadius has broadened its focus to include treasury, record-to-report, B2B payments, and account reconciliation.
- HighRadius as a Gartner Quadrant leader offers 70% efficiency improvement out-of-the-box, reaching up to 90% within six months.
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Medium
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397
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Complete JavaScript Road Map
- JavaScript road map covers various topics like variables, data types, control structures, functions, objects and arrays, classes and prototypes, error handling, asynchronous JavaScript, modules, event handling, DOM manipulation, regular expressions, browser and web APIs, functional programming, ES6+ features, Browser Object Model, Node.js concepts, testing frameworks, and more.
- Some good resources to learn JavaScript include documentation from Mozilla MDN Web Docs and DevDocs, as well as useful YouTube channels like 'JavaScript Daily', 'The Coding Diaries', and 'Learn Programming'.
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