Deep Learning with PyTorch Course
Deep Learning with PyTorch Course
PyTorch is the most popular Deep Learning framework. In the past years it has become the go to library for Deep Learning leaving TensorFlow (Keras) behind both in the industry and the research.
This course is an introduction to PyTorch for Deep Learning. It suits both data scientists with some experience with Keras who want to shift to PyTorch and Data scientists doing their first steps in the Deep Learning world.
The PyTorch Course is built with Jupyter Notebooks for interactive learning. It includes Home Exercises with reference solutions.
The PyTorch Course:
- Introduces the concept of Deep Learning and its building blocks.
- Introduces PyTorch and how to use it in the context of Deep Learning.
- Uses interactive learning based on Notebooks and real world problems.
- Includes self exercises with reference solutions.
- Python (Basic).
- Pandas.
- SciKit Learn.
- Recommended: Naya Data Science Course.
- Data scientists.
- NAYA College Data Science Course Graduates.
- Deep Learning Overview
- Origins.
- Deep Learning vs. Classic Machine Learning.
- Introduction to PyTorch
- Building Blocks.
- Comparison to TensorFlow / Keras.
- The Training Loop Concept.
- Neural Networks
- Classification Neural Network.
- Regression Neural Network.
- Auto Encoders.
- Optimizing the Training Loop
- Optimizers.
- Schedulers.
- Convolutional Neural Networks
- Convolution Block.
- Image Labeling.
- Image Segmentation.
רועי הינו בוגר MSc בהנדסת חשמל ומחשבים מהטכניון. מתמחה בעיבוד אותות, עיבוד תמונה, ראיה ממוחשבת, למידת מכונה (למידה עמוקה) שערוך ואופטימיזציה. רועי מדורג מקום 2 בעולם בקהילת Signal Processing StackExchnage (ה- StackOverflow של עולם עיבוד אותות ותמונה).
- טרם נקבע מועד פתיחה
- 09:00-16:30ימים ושעות
- 48 שעות אקדמיות
- בסיסירמת הקורס
- עבריתשפת הדרכה
- לבדיקת התאמה לקורס
- ממליצים
- לפתיחה והורדת סילבוס