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Embedded Systems Engineer and Certified Tensorflow Developer with a strong technical/coding background, including C, C++, Java, Python and Assembly. Additionally skilled back-end development based on Spring/Django Framework, and Machine Learning with Tensorflow and Pytorch.
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.
Founder, Principal Software Engineer. My personal website is https://www.justin.guru. Here are some of the many things I can help you with:
AWS: ECS, S3, EC2, Amplify
Azure: Most things
GCP: Most things
CI/CD: Pipelines, GitHub Actions, Jenkins
Containerization: Docker, Docker Compose
Languages: JavaScript, Typescript, Perl, PHP, Python
JS: Next.js, React, Redux, Angular, Vue, Nuxt.js, Svelte, D3, Express, Node, Webpack
Mobile: Expo, React Native, Cordova, Ionic
Styles: CSS, LESS, SASS, SCSS, Tailwind, Bootstrap
DBs: MongoDB, Firebase, Postgres, SQL, MySQL, DynamoDB
Testing: Jest, Karma, Jasmine, Mocha
SSO: Auth0, Azure A/D, GCP, AWS
Other: Moodle, InVision, Lottie, Figma, Adobe CC, PowerBI, K8s
Over 12 years of Experienced Mobile, Web, Machine Learning and Deep Learning Application developer and architect with a demonstrated history of working in the information technology and services industry. Skilled in Python, Tensorflow, Keras, Dart & Flutter, React, React Native, Node & Express, PHP & Laravel Framework, MySQL, Mongodb, Javascript, Angular, Kotlin (Android), Swift (iOS), AWS EC2, AWS Lightsail.
Also have a vast experience in developing human resource by providing training on above mentioned technologies.
Here is my Codecanyon profile : https://codecanyon.net/user/_lutfor
Here is my Udemy profile : https://www.udemy.com/user/lutfor-rahman-11/
Github : https://github.com/contactlutforrahman
Hacker Rank : https://www.hackerrank.com/_lutfor
LeetCode : https://leetcode.com/_lutfor
Jagbir RPA Solution Architect - Certified in UiPath and MS Power Platform
Have 13 years of IT experience in the analysis, design, development, integration, testing, and maintenance using ASP .NET, C#, and SQL Server.
Extensively worked on creating end to end Robotics Process Automation strategy for applications that includes
web, desktop, mainframe, PDF files using Microsoft, Google OCR’s, SharePoint, excel using UiPath.
• Delivered 100+ RPA UiPath bots. Project managed and delivered successfully across the globe where major was from US.
• Have experience in Microsoft Power Platform – MS Automate Flows and Desktop, Power virtual agent, and Power Apps
I love to teach what I know. I think I can explain things easily with examples. I have working as a Software Engineer for the last 5 years and have worked with some of the world's most reputed companiess like **Open AI, Scale AI, Doloras Lab** etc as a freelancer.
See the power of our Machine Learning tutors through glowing user reviews that showcase their successful Machine Learning learning journeys. Don't miss out on top-notch Machine Learning training.
“I've gotten a lot of help from Benign, and he had answers to all my questions, he is very knowledgeable in many areas in algorithms, in advanced coding on Java and Python, and also very good in CI/CD. He is very helpful and nice. Everything is looking good. Thank you.“
myname / Jun 2024
Benign John Ihugba
Machine Learning tutor
“Trenton is beast mode with machine learning. He was able to get me unstuck from a rut I was in for days in an hour. I highly recommend him as a mentor!“
Annie Cushing / Mar 2024
Trenton McKinney
Machine Learning tutor
“Gopal grasped the idea of the question quick and had some related examples from his work. Help me better simplify my thought on the problem“
Joel Beaufond / Mar 2024
Gopal Chitalia
Machine Learning 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
Machine Learning tutor
How to find Machine Learning tutors on Codementor
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We'll help connect you with a Machine Learning tutor that suits your needs.
Find the most suitable Machine Learning tutor by chatting with Machine Learning experts.
Arrange regular session times with Machine Learning tutors for one-on-one instruction.
Frequently asked questions
Learning Machine Learning 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 Machine Learning. 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 Machine Learning, 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 Machine Learning 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 Machine Learning through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Machine Learning skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Machine Learning in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Machine Learning 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 Machine Learning 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 Machine Learning 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 Machine Learning’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Machine Learning generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Machine Learning, contributing to major projects, and possibly specializing in specific areas within Machine Learning.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Machine Learning. Engaging with new developments, tools, and methodologies in Machine Learning 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 Machine Learning 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 Machine Learning 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 Machine Learning 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 Machine Learning 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 Machine Learning, 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 Machine Learning 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 Machine Learning 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 Machine Learning in a structured, supportive, and effective environment.
Personalized Machine Learning 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 Machine Learning.