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I love to teach what I know. I think I can explain things easily with examples. I have been working as a Software Engineer for the last 5 years and have worked with some of the world's most reputed companies like **Open AI, Scale AI, Doloras Lab**, etc as a freelancer.
*Need a boost in your skills or results?*
*Read my profile before hiring.*
I bring expertise in delivering high-quality projects and results using a wide range of technologies and tools:
- *Programming & Development*:
- *General Purpose Languages*: Python (Machine Learning, CNN, Keras, LSTM, PyTorch, Pandas, NumPy), C/C++, Java, R, Assembly, MATLAB, Rust, Go, and Kotlin.
- *Web Development*: JavaScript (ES6+), TypeScript, PHP, Perl, Ruby, and Elixir.
- *Scripting and Automation*: Shell scripting (Bash), PowerShell, Lua, and Tcl.
- *Mobile Development*: Swift (iOS), Dart (Flutter), React Native, Ionic, and Objective-C.
- *Frontend Technologies*: React.js, Vue.js, Angular, Svelte, Next.js, and Bootstrap.
- *Backend & API Development*: Node.js, Express.js, Django, Flask, Ruby on Rails, ASP.NET, FastAPI, and GraphQL.
- *Database Management*: MySQL, PostgreSQL, MongoDB, SQLite, Firebase, MariaDB, Redis, and Cassandra.
- *Software*: C#, Asp.net
- *Machine Learning & AI*: Tensorflow, Pytorch, OpenAI, Computer Vision, NLP, Python, sci-kit, Image processing
- *DevOps & Cloud*: Docker, Kubernetes, Jenkins, Terraform, Ansible, AWS (EC2, Lambda, S3, DynamoDB), Azure, and Google Cloud Platform (GCP).
- *Tools & Platforms*: LaTeX, Excel (advanced functions, VBA), Jupyter Notebooks, Power BI, MS Power Automate, Tableau, and Elasticsearch.
- *Miscellaneous Skills*:
- *Automation*: Selenium, Beautiful Soup, Puppeteer.
- *Data Analysis & Visualization*: Matplotlib, Seaborn, D3.js.
- *Version Control & Collaboration*: Git, GitHub, GitLab, Bitbucket.
- *Software Development Methodologies*: Agile/Scrum, Test-Driven Development (TDD).
I can assist you with:
- Adding *extra hands* to your team to speed up development.
- *Reviewing, debugging, and optimizing* your code for performance and maintainability.
- *Collecting, analyzing, and visualizing data* to build insightful reports, presentations, and dashboards.
My ultimate goal is to *over-deliver* and ensure you're 100% satisfied with the results.
If my profile resonates with your needs, feel free to send me a message. Let's bring your project to the next level together!
Hello everyone, I have been working in the CS industry for ~10 years. I have mainly been working on back-end and research oriented projects involving image processing. If you are looking for understanding how computers work at a deep level (as far as assembly), or want to know how big tech companies (such as Amazon) scale their projects, then I have knowledge to share with you!
Experienced software architect and developer with over a decade of expertise in building cloud-based applications. I specialize in web development, creating scalable, high-performance solutions, and have extensive experience in machine learning, including developing predictive models and integrating AI features to enhance applications.
Proficient across the full software development lifecycle, I excel at understanding complex codebases, addressing bugs, refactoring for performance, and implementing new features to meet evolving requirements. Committed to Object-Oriented Programming principles and design patterns, I ensure code is clean, maintainable, and scalable.
I focus on delivering well-tested, reliable solutions that support long-term success. My expertise in machine learning enables data-driven decision-making, while my .NET skills meet demanding technical requirements. I thrive in collaborative environments, valuing open communication and innovative problem-solving. Driven by a passion for technical excellence, I consistently deliver solutions that align with user needs and business goals.
Hello, my name is Silvia, I have a proven track record of leading AI teams and experiments
from ideation to production, and I bring a unique blend of passion, curiosity, enthusiasm, practical expertise, and theoretical knowledge to my work.
I hold a Master of Science in Computer Engineering with a specialization in Artificial Intelligence and have over 10 years of experience in Computer Vision, Deep Learning and Machine Learning, spanning both academia (EPFL) and industry. My journey includes roles as a Research and Scientific Assistant in academia and contributions in to both large enterprises and startups in the industry.
I thrive on making complex ideas accessible and actionable, whether through mentoring, consulting, or delivering practical implementations.
If you are a student eager to learn the fundamentals of AI, improve your coding skills, or navigate the nuances of advanced machine learning concepts, I am here to help you.
For businesses and startups, I offer tailored solutions and expert insights to help you harness the power of AI and machine learning for your projects.
6 years of experience in building and managing AI Systems.
* I develop end-to-end AI systems from requirements analysis, and data gathering to deployment, implementing new methods/research papers, and turning projects into research outcomes. I have achieved substantial performance in DL/ML/RL models for CV and NLP domain problems.
* Implementing and deploying projects handling and maintaining scalability, research papers as well as POCs.
* Project planning, requirements gathering, and analysing requirements to define the system's architecture, and implementation timeline.
* Provide mentoring to junior developers for ML projects.
Website: [roshantanisha.github.io/?ref=codementor](http://roshantanisha.github.io/?ref=codementor)
Summary:
I like to work on technology that is smart, simple and sophisticated. This sums up the vast knowledge required to work on projects to excel in a working product. I like to train Deep Neural Networks and understand them well.
I have mentored many students for their AI careers, teaching them Machine Learning and Mathematics. I am a mentor for the RFS (Reach for the Stars) Programme by the Aga Khan Education Board for India. I am an alumnus of this program as well.
I have a cumulative experience of 6 years working in the product and service-based industry for creating Machine Learning projects.
I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working on.
Highly Experienced in Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, and Algorithms, including models in the production environment, and deploying ML models. Working with top Indian colleges like BITS, niche NLP and CV, real-estate startups, MNCs, and Fortune top 20 companies, working with sensitive anonymized datasets, and creating state-of-the-art models are some of my achievements. I have strong and correct knowledge of Deep Learning concepts from the above experiences.
See the power of our Computer Vision tutors through glowing user reviews that showcase their successful Computer Vision learning journeys. Don't miss out on top-notch Computer Vision training.
“Great, figured it was a memory leak issue but couldnt explain it to myself properly. she helped explained the memory leak issue to me and another possible issue and is currently working to get to the bottom of it and we are working on our first of many future projects together.“
ChrisG / Jul 2024
Tanisha Bhayani
Computer Vision tutor
“It was good, she explaining the concepts well, but she had problem in the internet connection... hopefully next time avoid this problem.“
Arwa / Feb 2024
Tanisha Bhayani
Computer Vision tutor
“He helped me to add some new features to my game with Python and explained everything he did. He takes you into the process“
K. / Mar 2023
vishnu
Computer Vision tutor
“Moeed has been an excellent help and an efficient mentor in explaining the adjustments he made to the code. I will definitely consult with him moving forward and highly recommend him to everyone! Thanks Moeed :)“
deleted / Jun 2021
Moeed Shaik
Computer Vision tutor
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We'll help connect you with a Computer Vision tutor that suits your needs.
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Arrange regular session times with Computer Vision tutors for one-on-one instruction.
Frequently asked questions
How to learn Computer Vision?
Learning Computer Vision effectively takes a structured approach, whether you're starting as a beginner or aiming to improve your existing skills. Here are key steps to guide you through the learning process:
Understand the basics: Start with the fundamentals of Computer Vision. You can find free courses and tutorials online that cater specifically to beginners. These resources make it easy for you to grasp the core concepts and basic syntax of Computer Vision, laying a solid foundation for further growth.
Practice regularly: Hands-on practice is crucial. Work on small projects or coding exercises that challenge you to apply what you've learned. This practical experience strengthens your knowledge and builds your coding skills.
Seek expert guidance: Connect with experienced Computer Vision tutors on Codementor for one-on-one mentorship. Our mentors offer personalized support, helping you troubleshoot problems, review your code, and navigate more complex topics as your skills develop.
Join online communities: Engage with other learners and professionals in Computer Vision through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Computer Vision skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Computer Vision in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Computer Vision is continually evolving, staying informed about the latest developments and advanced features is essential. Follow relevant blogs, subscribe to newsletters, and participate in workshops to keep your skills up-to-date and relevant.
How long does it take to learn Computer Vision?
The time it takes to learn Computer Vision depends greatly on several factors, including your prior experience, the complexity of the language or tech stack, and how much time you dedicate to learning. Here’s a general framework to help you set realistic expectations:
Beginner level: If you are starting from scratch, getting comfortable with the basics of Computer Vision typically takes about 3 to 6 months. During this period, you'll learn the fundamental concepts and begin applying them in simple projects.
Intermediate level: Advancing to an intermediate level can take an additional 6 to 12 months. At this stage, you should be working on more complex projects and deepening your understanding of Computer Vision’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Computer Vision generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Computer Vision, contributing to major projects, and possibly specializing in specific areas within Computer Vision.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Computer Vision. Engaging with new developments, tools, and methodologies in Computer Vision is a continuous process throughout your career.
Setting personal learning goals and maintaining a regular learning schedule are crucial. Consider leveraging resources like Codementor to access personalized mentorship and expert guidance, which can accelerate your learning process and help you tackle specific challenges more efficiently.
How much does it cost to find a Computer Vision tutor on Codementor?
The cost of finding a Computer Vision tutor on Codementor depends on several factors, including the tutor's experience level, the complexity of the topic, and the length of the mentoring session. Here is a breakdown to help you understand the pricing structure:
Tutor experience: Tutors with extensive experience or high demand skills in Computer Vision typically charge higher rates. Conversely, emerging professionals might offer more affordable pricing.
Pro plans: Codementor also offers subscription plans that provide full access to all mentors and include features like automated mentor matching, which can be a cost-effective option for regular, ongoing support.
Project-based pricing: If you have a specific project, mentors may offer a flat rate for the complete task instead of an hourly charge. This range can vary widely depending on the project's scope and complexity.
To find the best rate, browse through our Computer Vision tutors’ profiles on Codementor, where you can view their rates and read reviews from other learners. This will help you choose a tutor who fits your budget and learning needs.
What are the benefits of learning Computer Vision with a dedicated tutor?
Learning Computer Vision with a dedicated tutor from Codementor offers several significant benefits that can accelerate your understanding and proficiency:
Personalized learning: A dedicated tutor adapts the learning experience to your specific needs, skills, and goals. This personalization ensures that you are not just learning Computer Vision, but exceling in a way that directly aligns with your objectives.
Immediate feedback and assistance: Unlike self-paced online courses, a dedicated tutor provides instant feedback on your code, concepts, and practices. This immediate response helps eliminate misunderstandings and sharpens your skills in real-time, making the learning process more efficient.
Motivation and accountability: Regular sessions with a tutor keep you motivated and accountable. Learning Computer Vision can be challenging, and having a dedicated mentor ensures you stay on track and continue making progress towards your learning goals.
Access to expert insights: Dedicated tutors often bring years of experience and industry knowledge. They can provide insights into best practices, current trends, and professional advice that are invaluable for both learning and career development.
Career guidance: Tutors can also offer guidance on how to apply Computer Vision in professional settings, assist in building a relevant portfolio, and advise on career opportunities, which is particularly beneficial if you plan to transition into a new role or industry.
By leveraging these benefits, you can significantly improve your competency in Computer Vision in a structured, supportive, and effective environment.
How does personalized Computer Vision mentoring differ from traditional classroom learning?
Personalized Computer Vision mentoring through Codementor offers a unique and effective learning approach compared to traditional classroom learning, particularly in these key aspects:
Customized content: Personalized mentoring adapts the learning material and pace specifically to your needs and skill level. This means the sessions can focus on areas where you need the most help or interest, unlike classroom settings which follow a fixed curriculum for all students.
One-on-one attention: With personalized mentoring, you receive the undivided attention of the tutor. This allows for immediate feedback and detailed explanations, ensuring that no questions are left unanswered, and concepts are fully understood.
Flexible scheduling: Personalized mentoring is arranged around your schedule, providing the flexibility to learn at times that are most convenient for you. This is often not possible in traditional classroom settings, which operate on a fixed schedule.
Pace of learning: In personalized mentoring, the pace can be adjusted according to how quickly or slowly you grasp new concepts. This custom pacing can significantly enhance the learning experience, as opposed to a classroom environment where the pace is set and may not align with every student’s learning speed.
Practical, hands-on learning: Mentors can provide more practical, hands-on learning experiences tailored to real-world applications. This direct application of skills is often more limited in classroom settings due to the general nature of the curriculum and the number of students involved.
Personalized mentoring thus provides a more tailored, flexible, and intensive learning experience, making it ideal for those who seek a focused and practical approach to mastering Computer Vision.