Deep Learning Engineer
By Jonathan Street
Learn how to build and apply deep learning to real world problems

Target skills

debugging
PyTorch
TensorFlow
transfer learning
deep learning
neural networks
Introduction to Deep Learning & Neural Networks with Keras
5 weeks
Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will......

What are Convolutional Neural Networks (CNN / Convnets)
8 minutes
#CNN #ConvolutionalNeuralNetwork #MachineLearning #DeepLearning #DataScience We understand the working and the architecture of a general Convolutional Neural Network or Convnets. We look at each layer one by one. The Convolutional Layer, Max Pooling Layer, Normalization Layer, Fully Connected ......

What are Recurrent Neural Networks (RNN) and Long Short Term Memory Networks (LSTM) ?
8 minutes
#RNN #LSTM #DeepLearning #MachineLearning #DataScience #RecurrentNerualNetworks Recurrent Neural Networks or RNN have been very popular and effective with time series data. In this tutorial, we learn about RNNs, the Vanishing Gradient problem and the solution to the problem which is Long short ......

Keynote - Malte Pietsch: Transfer Learning - Entering a new era in NLP | PyData Warsaw 2019
45 minutes
Transfer learning has been changing the NLP landscape tremendously since the release of BERT one year ago. Transformers of all kinds have emerged, dominate most research leaderboards and have made their way into industrial applications. In this talk we will dissect the paradigm of transfer learni......

How to Implement Deep Learning Papers | DDPG Tutorial
1.9 hours
I'll show you how I went from the deep deterministic policy gradients paper to a functional implementation in Tensorflow. This process can be applied to any deep learning paper (computer vision, natural language processing, generative adversarial networks, etc.), not just deep reinforcement learn......

Building Deep Learning Models Using PyTorch
3.3 hours
PyTorch is an open source, deep learning framework which is a popular alternative to TensorFlow and Apache MXNet. PyTorch APIs follow a Python-native approach which, along with dynamic graph execution, make it very intuitive to work with for Python developers and data scientists. In this course, ......

How To Debug Deep Learning Programs | A Simple Process Anybody Can Use
18 minutes
Dimensional mismatch problems in deep learning programs can be a pain to debug, but I'll show you a simple and repeatable process for dealing with them head on. This comes from an old issue in my github that turns out to be related to a version mismatch with PyTorch. Rather than tell the person ......

Introducing TensorWatch: Microsoft Research New Tool for Debugging Deep Learning Programs
5 minutes
Debugging is one of the most difficult aspects in the lifecycle of deep learning problems. The recent advancements in deep learning frameworks have lowered the entry point for creating really sophisticated models that are both effective and hard to interpret at the same time. Very often, research......

Target skills

debugging
PyTorch
TensorFlow
transfer learning
deep learning
neural networks