Introduction to Deep Learning
In this class you’ll learn about machine learning’s most flexible family of model: neural networks. You’ll build neural networks using Tensorflow. Manage and manipulate datasets using Pandas; and how to manage and mitigate common sources of error and failure in deep learning systems.
At a glance:
Appropriate for current programmers, data analysts, and statisticians.
3 days worth of class time.
Focus on fundamental concepts in meaningful detail including:
Neural networks as Universal Function Approximators.
Neural network architectures, patterns and best practices.
Key layer types, including dense, dropout, and batch normalization.
Training and data preprocessing tools like checkpointing, early stopping, and scaling/normalization.
Course Objectives
By the end of this class students will be able to:
Build and train neural networks using Tensorflow.
Describe the inner workings of neural networks.
Utilize data preprocessing techniques to maximize neural network effectiveness.
Deploy ML models to simple web servers.
Prerequisites
Beginner to Intermediate level Python.
Comfortable with math (or at least not scared of it).
Bonus points for specific familiarity with:
The derivative from calculus.
High school level statistics.
Multidimensional spaces (linear algebra).
Fundamental ML concepts such as test/train/validation splits and gradient descent.
Classroom Experience
Teb’s Lab courses have an emphasis on hands-on education. This class is organized around a repeated 3-step pattern:
First, your instructor will provide a walkthrough of a snippet of Python code. This will involve line by line analysis of the code, use of a debugger to examine the state of the code after each line executes, and “micro-exercises” to allow students to test their understanding and apply the new concepts.
Second, students will tackle a longer exercise. These exercises will challenge students to apply the concepts and — as the course progresses — combine new knowledge with previously acquired skills. During these exercises students will receive direct support and feedback from the instructor.
Third, students will see and share solutions to the exercise. One solution will be provided by the instructor. Additionally, students will be invited to share their own solutions. Those who do will receive the gift of additional feedback from their peers and the instructor. Those who do not will still have the opportunity to give feedback, and learn from their peers’ work.
Courses with Teb’s Lab are keenly focused on a class atmosphere that is:
Interactive and challenging; wrestling with tough concepts is a cornerstone of learning.
Welcoming and inclusive; safety and comfort allow learners to be present and engaged.
Fun and interesting; boredom is the bane of education.
Logistics and Pricing
Teb’s Lab classes are delivered over Zoom.
We charge a flat rate of $600 per classroom hour.
With a full class of 20 students this is only $30 per student per hour.
This class is capped at 20 students per session.
How To Book This Class
Click here to schedule a free consultation regarding this course. Your consultation will be with the instructor who will teach the class. During the consultation we’ll discuss scheduling and logistics, answer any questions you have about the course, and (if you book a class) discuss payment.
We do not book any courses without a consultation to ensure alignment on course goals and delivery logistics.
Book a Consultation Now
Consultations are completely free and carry no obligation. During the consultation we’ll answer any questions you have about the course, discuss scheduling and logistics, and discuss payment. Your consultation will be with the instructor who would teach the class.