Applied Mathematics for Machine Learning and Deep Learning: Theory and Practice
A partir de 43.03 $ /h
This course covers the application of mathematics in machine learning and deep learning. It introduces students to fundamental mathematical concepts such as linear algebra, calculus, probability theory, and optimization. The course then explores various machine learning algorithms and deep learning models, including supervised and unsupervised learning, neural networks, and deep learning architectures. Students gain hands-on experience through programming assignments and projects using popular libraries like TensorFlow or PyTorch. The course emphasizes the mathematical foundations of these techniques, enabling students to understand and analyze their performance. By the end of the course, students will be proficient in applying mathematics to solve real-world problems in machine learning and deep learning.
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Conectado desde Marruecos
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I am a PhD student in Applied Mathematics specializing in Machine Learning and Deep Learning. With my extensive qualifications and experience in teaching in the supplementary course sector, I am offering comprehensive mathematics support courses for students at all levels. My teaching approach focuses on an easy-to-understand pedagogical method that ensures efficiency and effectiveness in learning.
Formación
baccalaureate in Mathematical sciences/ 2014
A professional license in teaching mathematics ENS/ 2017
Master of Mathematics and its applications FST /2019
PHD student in Math // AI
A professional license in teaching mathematics ENS/ 2017
Master of Mathematics and its applications FST /2019
PHD student in Math // AI
Experiencia / Calificaciones
I Am a PHD student in mathematics
qualified and experienced, with experience in teaching in the supplementary course sector
I am currently a teacher in the private sector: high school
Experienced Maths Home tutor ...
qualified and experienced, with experience in teaching in the supplementary course sector
I am currently a teacher in the private sector: high school
Experienced Maths Home tutor ...
Edad
Adolescentes (13-17 años)
Adultos (18-64 años)
Tercera edad (65+ años)
Nivel del estudiante
Principiante
Intermedio
Avanzado
Duración
60 minutos
La clase se imparte en
inglés
francés
Habilidades
Disponibilidad en una semana típica.
(GMT -05:00)
Nueva York
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Garantía del Buen Profesor