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Working in the IT sector for more than 10 years.
With over 10 -years of freelancing and professional experience taught me all kinds of frameworks and languages, ranging from React, Angular, Vue, Node js, Express js, React Native, Redux, Rx JS, JavaScript, Typescript, WordPress, PHP, MySQL, MongoDB, Firebase, Sqlite, Postgresql, ES5+, Python3, Machine Learning, Deep Learning, RNN, CNN, C/C#/C++, .Net, Assembly, VBA, VB, Excel Macro, Java, Spring Boot Micro-services, R, Shiny, STATA, MATLAB, Google Sheet, App Script, Bubble io, etc.
Over my long career, I have come across all kinds of challenges and gained vast experience with different kinds of industries like portals, medical industry, perception exercise, employee management, etc.
I have good experience with frontend development using React JS along with Typescript, Firebase, GraphQL, React Native, Native Script, React, Material UI, Ionic, Node.js, Web Sockets, and real-time communication.
I have also worked on containerization technologies like Kubernetes, Docker, AWS, GCP, Azure etc.
I am very good with backend technologies as well like Java Spring boot, microservices, MySQL, Postgres, Elasticsearch, AWS/Google integration.
Please contact me to get the result done in a professional way.
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.
Production systems fire fighter - there is nothing I cannot debug.
I will not do your homework.
Member of Mensa & Intertel, backwoods enthusiast. Human languages for fun, programming languages for breakfast. I left Detroit in the Dot-Com era to live deep in a north woods cabin w/my animal family.
I solve my own problems with grace and efficiency. I'll be happy to solve yours!
My five most valuable skills:
* Anticipation (of variables and user expectations)
* Debugging
* Machine logic
* Problem solving
* Versatility
These skills when applied to any challenge, design or technology stack, have consistently produced efficient and reliable results across an unlimited technology stack since childhood.
What I enjoy most about Code Mentor:
Utilizing my unique skill set to solve a diverse set of challenging critical issues for people in a bind. My most satisfying sessions solve very difficult and unique situations for those who have already exhausted their available human and intellectual resources.
FAQ
* No, I am not a robot. But my bots might be one day.
* No, I will not travel anywhere , unless you provide a space ship or parachute.
* I try to make a record of all changes and be able to revert them quickly, but it is your responsibility to archive responsibly
** SUPPORT SPECIALTIES **
- AWS Anything
- Dedicated support through to resolution
- Defensive cyber security
- Disaster recovery
- Emergency response for mission-critical systems
- High pressure environments
- Forensics / electronic discovery
Check out my video course on pfSense!
https://www.packtpub.com/product/hands-on-pfsense-2-x-for-firewalls-and-routers-video/9781789805017
I am a data scientist in the genomics area, and I hold a PhD degree in Epigenomics, a field of Bioinformatics. I love to teach and pass along knowledge!
**R** and **bash** are my main languages, and I work with data analysis, statistics, and bioinformatics.
Under the bioinformatics umbrella, my areas of expertise are:
- **Transcriptomics** (RNA-seq and Affymetrix microarray);
- **Population genomics** (GWAS)
- **DNA methylation sequencing** (ERRBS and Infinium methylation);
Blog: [flaviaerius.com](http://flaviaerius.com)
[**Understand Linear Regression Results in R**](https://flaviaerius.netlify.app/posts/linear-regression-coefs/)
[**Stuck in an error message? Let me help you fix it!**](https://flaviaerius.netlify.app/2022/06/14/tips-to-fix-programming-error/)
[**7 tips for academic researchers on their way to Data Science**](https://flaviaerius.netlify.app/2022/08/10/7-tips-for-academic-researchers-on-their-way-to-data-science/)
Specialist in GCP services. Experience in Data Engineering since 2010. Applied Data/machine learning engineer using python for the last few years. Understanding data and applying the ML algorithm to solve use cases include data preparation. Also expertise in making pipeline for data related projects.
See more: **https://subhadip.ca**
- In my career I worked in multiple roles (Software Developer, Software Architect, User Experience Designer, Consultant).
- I'm eager to understand problems in full detail to come up with the best solution (in terms of time/budget/quality).
- Creator of open source project goodplay, an Ansible-/Docker-based testing tool.
See the power of our Docker Machine tutors through glowing user reviews that showcase their successful Docker Machine learning journeys. Don't miss out on top-notch Docker Machine training.
“Great session with Anar. He was able to troubleshoot my Docker issues and teach me along the way. Very knowledgeable!“
Aria / Jan 2023
Anar Jafarov
Docker Machine tutor
“Joel is a really knowledgeable guy with a lot of interesting experience in the games industry. I got some great direction for my projects and was able to get a deeper understanding of what was required to work in the games industry. I can highly recommend Joel!“
Zeshan Rasul / Jun 2024
Joel Gompert
Docker Machine tutor
“David is an excellent mentor in C++. He has a clear and thorough way of explaining concepts that makes even complex topics easy to understand. Working with him has helped improved my understanding of C++. Highly recommend him if you're looking to deepen your programming skills!“
Aaron Kay Kavanaugh / Jun 2024
David Brown
Docker Machine tutor
“Angel is a good mentor that taught me step by step in my first lesson with Java, he gave the necessary tools for starting and setting my workplace, he also gave some useful advice for my first program in Java, most probably I will get other session with him.“
Nelson Garcia / Jun 2024
Ángel quintanilla
Docker Machine tutor
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Frequently asked questions
Learning Docker Machine 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 Docker Machine. 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 Docker Machine, 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 Docker Machine 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 Docker Machine through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Docker Machine skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Docker Machine in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Docker Machine 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.
The time it takes to learn Docker Machine 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 Docker Machine 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 Docker Machine’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Docker Machine generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Docker Machine, contributing to major projects, and possibly specializing in specific areas within Docker Machine.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Docker Machine. Engaging with new developments, tools, and methodologies in Docker Machine 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.
The cost of finding a Docker Machine 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 Docker Machine 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 Docker Machine 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.
Learning Docker Machine 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 Docker Machine, 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 Docker Machine 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 Docker Machine 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 Docker Machine in a structured, supportive, and effective environment.
Personalized Docker Machine 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 Docker Machine.