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    Dave
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    Machine learning course / project by Doctor in machine learning and actuarial science

    Translated by Google. Click to view original.
    Hello,
    I am an experienced machine learning teacher with 5 years of expertise in teaching this discipline at all levels. My expertise using Python and R allows me to teach different machine learning algorithms such as neural networks, decision trees and clustering algorithms. I am also experienced in using popular Python and R libraries such as TensorFlow, Keras, Scikit-learn and ggplot2.
    In addition to my machine learning skills, I am able to help students read and understand research papers for their presentations, as well as work on projects in Python and R. My commitment to machine learning is passionate and I enjoy sharing my knowledge with my students.
    If you are interested in my services as a machine learning teacher for all levels, do not hesitate to contact me.
    In addition to my machine learning skills, I am also able to help you with mathematics, statistics and dissertation writing.
    I am available to teach the following subjects:
    1.Python or R
    2. Data exploration
    3.Machine learning
    3.1. Intro ML
    3.2. Linear Model
    -> Linear Models for Regression and Classification
    3.3. kernel
    -> Kernelization
    3.4. Model selection
    3.5. model set,
    -> Bagging / RandomForest, Boosting (XGBoost, LightGBM,...) , Stacking
    3.6. Data preprocessing
    -> Data pre-processing
    -> Pipelines: choose the right preprocessing steps and models in your pipeline
    -> Cross validation
    3.7. Neural Networks
    -> Neural architectures
    -> Training neural nets: Forward pass: Tensor operations and Backward pass: Backpropagation
    -> Neural network design: Activation functions, weight initialization and Optimizers
    -> Neural networks in practice: Model selection, Early stopping, Memorization capacity and information bottleneck, L1/L2 regularization, Dropout, Batch normalization
    3.8. Convolutional Neural Networks
    -> Convolved Image
    -> Convolutional neural networks
    ->Data increase
    -> Model interpretation
    -> Using pre-trained networks (transfer learning)
    3.9. Neural Networks for text
    -> Bag of word representations, Word embeddings, Word2Vec, FastText, GloVe

    Extra information

    Translated by Google. Click to view original.
    In addition to my teaching in machine learning, I can also help my students prepare for job interviews for data scientist positions.

    I am currently doing a doctorate in applied mathematics at Paris 1. I obtained my two master's degrees in statistics (at paris 1) and in machine learning (at INSA Rouen).

    My research work focuses on the application of machine learning techniques to statistical problems. I am passionate about applying mathematics and computer science to solving real-world problems.

    Location

    Online via webcam
    At teacher's location: Place de Clichy, Paris, France

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    General info

    Age:
    Children (7-12 years old)
    Teenagers (13-17 years old)
    Adults (18-64 years old)
    Seniors (65+ years old)
    Student level:
    Beginner
    Intermediate
    Advanced
    Duration:
    60 minutes
    The class is taught in:French, English

    About Me

    Translated by Google. Click to view original.
    I am passionate about applying mathematics and computer science to solving real-world problems.

    If you want to learn more about my professional background and skills. You will discover my professional experiences, achievements, and areas of interest there.


    I am passionate about applying mathematics and computer science to solving real-world problems.

    If you want to know more about my professional background and my skills. You will be able to discover my professional experiences, my achievements and my centers of interest.

    Education

    Translated by Google. Click to view original.
    I am currently pursuing a doctoral degree in applied mathematics at the University of Paris 1. I obtained my two master's degrees in statistics (at Paris 1) and machine learning (at INSA Rouen). My research work focuses on the application of machine learning techniques to statistical problems.


    I am currently doing a doctorate in applied mathematics at the University of Paris 1. I obtained my two master's degrees in statistics (at paris 1) and in machine learning (at INSA Rouen). My research work focuses on the application of machine learning techniques to statistical problems.

    Experience / Qualifications

    Translated by Google. Click to view original.
    I am a machine learning teacher with 5 years of experience and I am able to teach at all levels. I specialize in using Python and R to teach different machine learning algorithms, including neural networks, decision trees, and clustering algorithms.
    Hello ! If you're looking for a private Python tutor, you've come to the right place! I am a Python expert with several years of experience teaching this programming language. I can help you learn the basics of Python, as well as more advanced topics such as objects and classes. As a private teacher, I can adapt my lessons to your level and your individual needs to help you progress quickly. I can also show you how to use popular libraries like: NumPy: a library for scientific computing, which allows working with multidimensional arrays and performing high performance calculations. Pandas: a library for data analysis, which offers flexible and easy-to-use data structures for manipulating tabular data. Matplotlib: a library for data visualization, which allows you to create professional-quality graphs and figures. Scikit-learn: a library for machine learning, which offers supervised and unsupervised learning algorithms for data analysis. If you are interested, do not hesitate to contact me to discuss your needs and my availability. I look forward to working with you!

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    Availability of a typical week

    (GMT -04:00) New York
    MonTueWedThuFriSatSun
    0              
    1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
    2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
    3  Monday at 3:00  Tuesday at 3:00  Wednesday at 3:00  Thursday at 3:00  Friday at 3:00  Saturday at 3:00  Sunday at 3:00
    4  Monday at 4:00  Tuesday at 4:00  Wednesday at 4:00  Thursday at 4:00  Friday at 4:00  Saturday at 4:00  Sunday at 4:00
    5  Monday at 5:00  Tuesday at 5:00  Wednesday at 5:00  Thursday at 5:00  Friday at 5:00  Saturday at 5:00  Sunday at 5:00
    6  Monday at 6:00  Tuesday at 6:00  Wednesday at 6:00  Thursday at 6:00  Friday at 6:00  Saturday at 6:00  Sunday at 6:00
    7  Monday at 7:00  Tuesday at 7:00  Wednesday at 7:00  Thursday at 7:00  Friday at 7:00  Saturday at 7:00  Sunday at 7:00
    8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00  Saturday at 8:00  Sunday at 8:00
    9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00  Saturday at 9:00  Sunday at 9:00
    10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
    11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
    12  Monday at 12:00  Tuesday at 12:00  Wednesday at 12:00  Thursday at 12:00  Friday at 12:00  Saturday at 12:00  Sunday at 12:00
    13  Monday at 13:00  Tuesday at 13:00  Wednesday at 13:00  Thursday at 13:00  Friday at 13:00  Saturday at 13:00  Sunday at 13:00
    14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
    15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
    16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
    17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
    18              
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    from $55.17At teacher's location
    from $55.17Online via webcam

    Good-fit Instructor Guarantee


    If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

    Online reputation

    • Instructor since April 2023
    • Phone number verified
    • Google connected

    Availability of a typical week

    (GMT -04:00) New York
    MonTueWedThuFriSatSun
    0              
    1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
    2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
    3  Monday at 3:00  Tuesday at 3:00  Wednesday at 3:00  Thursday at 3:00  Friday at 3:00  Saturday at 3:00  Sunday at 3:00
    4  Monday at 4:00  Tuesday at 4:00  Wednesday at 4:00  Thursday at 4:00  Friday at 4:00  Saturday at 4:00  Sunday at 4:00
    5  Monday at 5:00  Tuesday at 5:00  Wednesday at 5:00  Thursday at 5:00  Friday at 5:00  Saturday at 5:00  Sunday at 5:00
    6  Monday at 6:00  Tuesday at 6:00  Wednesday at 6:00  Thursday at 6:00  Friday at 6:00  Saturday at 6:00  Sunday at 6:00
    7  Monday at 7:00  Tuesday at 7:00  Wednesday at 7:00  Thursday at 7:00  Friday at 7:00  Saturday at 7:00  Sunday at 7:00
    8  Monday at 8:00  Tuesday at 8:00  Wednesday at 8:00  Thursday at 8:00  Friday at 8:00  Saturday at 8:00  Sunday at 8:00
    9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00  Saturday at 9:00  Sunday at 9:00
    10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
    11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
    12  Monday at 12:00  Tuesday at 12:00  Wednesday at 12:00  Thursday at 12:00  Friday at 12:00  Saturday at 12:00  Sunday at 12:00
    13  Monday at 13:00  Tuesday at 13:00  Wednesday at 13:00  Thursday at 13:00  Friday at 13:00  Saturday at 13:00  Sunday at 13:00
    14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
    15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
    16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
    17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
    18              
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    20              
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    22              
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    from $55.17At teacher's location
    from $55.17Online via webcam

    Good-fit Instructor Guarantee


    If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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