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Founded in 2017, our team at TLVTech is an all-around technology partner that helps businesses scale and conquer their goals. We are a team that’s committed to supporting all kinds of businesses, creating solutions for various functions, and providing insightful consultations to best streamline operations. We let our clients have full focus on their core functions while we handle their tech needs.
With that being said, we’re extremely excited to announce fantastic news that was made possible by our gracious clients. Just recently, TLVTech won The Manifest Company Award for the most reviewed and recommended B2B partner in New York City this 2024! According to their latest report, our team is among the city’s finest leaders for the following services:
The Manifest is a business news and how-to website from Washington DC. The resource is known for its annual award cycle that aims to spotlight outstanding service providers across different industries worldwide. The awardees are chosen based on quantitive criteria that focus on the volume of honest testimonials and endorsements each firm earned over the preceding twelve months.
We’d like to seize this opportunity to express our sincerest gratitude to our invaluable clients. Your support is what helped us unlock this milestone.
On behalf of the entire TLVTech team, thank you so much for believing in us!
Interested to know more about our work? Connect with TLVTech and let’s schedule a meeting for your project.
TLVTech is proud to rank as a 2024 leader in cloud, React Native, and machine learning services, thanks to SuperbCompanies' recognition.
- Machine Learning (ML) is a type of Artificial Intelligence (AI) that enables systems to learn from data. - ML dates back to the 1950s, but its significance has grown with the rise of AI. It allows machines to learn without extensive programming. - There are three key types of ML: supervised learning (machine learns from tagged data), unsupervised learning (machine finds patterns in raw data), and reinforcement learning (machine self-corrects through trial and error). - ML has wide applications, like healthcare (predicting patient outcomes), finance (predicting market trends), spam filters, and recommendation systems (Netflix). - Deep learning is a subset of ML that learns from data and is a key component of future advancements in ML. - To start a career in ML, one can begin with online tutorials and courses. Certification programs, hands-on projects, and internships help advance one's career in ML. - ML fits into data science as a tool for understanding large data sets; it's a major component of AI's learning process. - ML is utilized in both AI and data science for tasks such as ETAs prediction for rides in Uber and curating tweets for Twitter users.
- Continuous Integration (CI) is a practice where developers consistently merge changes to the main branch, while Continuous Deployment/Delivery (CD) automates the software release process. - Jenkins is a beneficial tool for CI/CD as it's open-source, easy to install, has a wide range of plugins, and allows building across multiple platforms. - Setting up a Jenkins pipeline involves installing Jenkins, configuring source control settings, creating build triggers, defining test procedures and setting up automated deployments. - Jenkins can also be integrated with other DevOps tools like Docker for task automation, Kubernetes for managing your Docker containers, and GitHub for code storage. - For security, use Jenkins' access control features and keep your tools regularly updated. Manage pipeline failures with recovery scenarios or a fail-fast strategy. To enhance performance, use Jenkins' master/agent architecture and integrate it with Ansible, Docker, and Kubernetes.
