Find top XGBoost tutors - learn XGBoost today

Find top XGBoost tutors - learn XGBoost today

Master XGBoost from our XGBoost tutors, mentors, and teachers who will personalize a study plan to help you refine your XGBoost skills. Find the perfect XGBoost tutor now.

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Learn XGBoost with online tutors

  • Learn XGBoost with XGBoost tutors - Max Epstein

    Max Epstein

    XGBoost tutor

    US$35.00 /15 min
    30 reviews

    Machine Learning Engineer & Data Scientist. Advanced user of the Python libraries for data processing, predictive models, and visualization. AWS ML Specialty Certified. Passionate about elegant code, automation, and model explainability. And recently (past year), most interested and active in NLP and LLM applications, especially: \* custom document parsing/informatoin extraction, \* neural/hybrid search and \* Retrieval Augmented Generation (RAG) systems (e.g. chatbots informed by neural/hybrid search to reduce hallucination) on custom/private document sets. Highly adept at optimizing speed/performance of python data science workloads via just-in-time compilation strategies (numba, pypy, or even sometimes a rewrite in Julia), or horizontal scaling to distributed compute on cloud infrastructure. Though honestly that step is needed less frequently than most clients seem to expect; usually optimizing for code clarity, safety, and development iteration speed proves more valuable in my experience. Look forward to hearing from you if you have something that I'd find interesting and fun to work on.

  • Learn XGBoost with XGBoost tutors - Éderson André de Souza

    Éderson André de Souza

    XGBoost tutor

    US$25.00 /15 min
    16 reviews

    Python | Scala | LLM | Langchain | Machine Learning | Data Scientist | Computer Vision Passionate Data Scientist and Computer Vision Engineer with a proven track record of leveraging machine learning to create value-driven solutions that enhance company outcomes and customer experiences. Specializing in insurance underwriting models, I have demonstrated adaptability and a keen interest in exploring new domains. My expertise lies in building robust Python and Scala applications for diverse purposes, including production line inspections where I develop applications that capture real-time images from cameras, extracting crucial data for quality assurance and production metrics. Key Areas of Expertise: Data Science: Proficient in both Supervised and Unsupervised Learning, with a strong background in recommenders, forecasting, classification, and anomaly detection. Computer Vision: Skilled in image classification and object detection using Pytorch and TensorFlow, and experienced in utilizing OpenCV for various vision tasks. LLM: Utilizing LLM in conjunction with Langchain for RAG systems, focusing on task automation and interactions with APIs. Knowledge in: MLOps, Deep Learning, NLP, BI with Power-BI, and Insurance Underwriting Models. Main Tools: Python, Scala, Jupyter Notebooks, VS Code, Git, Numpy, Pandas, Sklearn, Pytorch, Airflow, DVC, MLFlow, Docker, OpenCV.

  • Learn XGBoost with XGBoost tutors - Manraj Singh

    Manraj Singh

    XGBoost tutor

    US$20.00 /15 min
    9 reviews

    I love Open Source and love contributing to projects and maintaining them. Apart from Open Source, I love mentoring students and sharing stories from my journey thus far. Find me on Github: https://github.com/ManrajGrover

  • Learn XGBoost with XGBoost tutors - Mateus Picanco

    Mateus Picanco

    XGBoost tutor

    US$15.00 /15 minfirst 15 mins free badge
    3 reviews

    Hello everyone! I'm Mateus, a full-stack **Data Scientist** from Brazil with a background in **Digital Signal Processing**. I graduated from **Brown University** in 2018 with a Bachelor of Science in **Electrical Engineering** and have been working in the Data domain ever since. I have experience with the full scope of the Data Science process, from building data pipelines and developing models to evaluating A/B tests for Data Products. I'm open to any mentorship opportunities related to data, especially when it comes to **Machine Learning**, **Natural Language Processing**, **Python**, and **Elasticsearch**. I am currently a Data Scientist at Microsoft and have previously worked at the largest investment bank in Latin America and at Telefonica. Throughout my career, I developed skills and projects in various segments, including Customer Segmentation, Next Best Offer models, and detection of rare events. I have over 4 years of experience in programming with Python, Machine Learning (especially when applied to CRM and Product Analytics), and Natural Language Processing. I also have solid experience implementing data orchestration and Elasticsearch-based analytics. Finally, I have been a mentor for both for-profit and non-profit organizations since I was 16 years old. I'm extensively trained in mentorship and tutoring and have mentored all kinds of people in many topics, from essay writing to machine learning.

  • Learn XGBoost with XGBoost tutors - Michał Dankiewicz

    Michał Dankiewicz

    XGBoost tutor

    US$15.00 /15 min
    3 reviews

    I have 7 years of professional experience in Python, doing machine learning and bringing it to production. Find me on Twitter @mdank_pl

  • Learn XGBoost with XGBoost tutors - Jorn Mossel

    Jorn Mossel

    XGBoost tutor

    US$20.00 /15 min
    1 reviews

    I hold PhD in Physics. Worked as a quant/data scientist for 10 years on wall st (ex-Goldman Sachs). Currently working in the energy space. Experienced in a wide range of machine learning applications (expert in time series analysis).

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    James D. Bartlett III

    XGBoost tutor

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    Learn XGBoost with XGBoost tutors - Stefano Maglione

    Stefano Maglione

    XGBoost tutor

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    Learn XGBoost with XGBoost tutors - Olamide Soyoye

    Olamide Soyoye

    XGBoost tutor

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    Learn XGBoost with XGBoost tutors - Kafil Ahmed

    Kafil Ahmed

    XGBoost tutor

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How to find XGBoost tutors on Codementor

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Frequently asked questions

How to learn XGBoost?

Learning XGBoost 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 XGBoost. 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 XGBoost, 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 XGBoost 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 XGBoost through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
  • Build real-world projects: Apply your XGBoost skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using XGBoost in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
  • Stay updated: Since XGBoost 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 XGBoost?

The time it takes to learn XGBoost 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 XGBoost 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 XGBoost’s more advanced features and best practices.
  • Advanced level: Achieving proficiency or an advanced level of skill in XGBoost generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of XGBoost, contributing to major projects, and possibly specializing in specific areas within XGBoost.
  • Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in XGBoost. Engaging with new developments, tools, and methodologies in XGBoost 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 XGBoost tutor on Codementor?

The cost of finding a XGBoost 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 XGBoost 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 XGBoost 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 XGBoost with a dedicated tutor?

Learning XGBoost 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 XGBoost, 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 XGBoost 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 XGBoost 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 XGBoost in a structured, supportive, and effective environment.

How does personalized XGBoost mentoring differ from traditional classroom learning?

Personalized XGBoost 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 XGBoost.

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