The questions in the Deep Learning online test will be multiple choice and may cover topics such as What is deep learning?,Curse of dimentionality,Machine learning vs deep learning,Use cases of deep learning,Human brain vs neural network,What is perceptron?,Learning rate,Epoch,Batch size,Activation function,single layer perceptron,Deep learning and its applications,Deep learning architectures,Deep learning for speech and audio processing,Deep learning for computer vision,Deep learning for natural language processing,Deep reinforcement learning,Mathematical Preliminaries and basics of programming,linear algebra,Probability and Statistics,Numerical optimization for ML,Data visualisation,Scalable programming using pyspark,Python programming POD,Paradigm of machine leaning,Supervised learning,Unsupervised learning,Tensor flow 2.0,Introduction to tensor flow 2.x,Installing tersor flow 2.x,Defining sequence model layers,Layer types,Model compilation,Model optimizer,Model loss function,Model trainning,Digital classification using simple neural network,Improving the model,Adding hidden layer,Adding dropout,Using Adam optimizer,Introduction to neural networks,Implementing gradient descent,Training neural networks,Deep learning with Pytorch,Convolutional neural network,Image classifications examples,Cloud computing,What is convolution,Convolutional layer network,Convolutional layer,Filtering,ReLU,Pooling,Data flattening,Fully connected layer,Predicting a cat or a dog,Saving and loading models,Face detection using open cv,CNNs in PyTorch,Weight Intialization,Autoencoders,Transfer learning in PyTorch,Recurrent neural network,Long short term memory network,Hyperparameters,Embedding and word2Vec,Sentiment prediction RNN,GAN,Which face is fake?,How does GAN work?,Step by step gan implementation,Types of gan,Deep convolutional gans,PIX2PIX,Introduction to deployment,Deploy a model,Amazon sagemaker,XG boost,How to deploy PyTorch model,Model monitoring,Monitoring the behaviour of model over time
Data Scientist
