Image Classification:Classifying the MNIST dataset with Convolutional Neural Networks

we will improve our handwritten digit recognizer which will implement it in week two. If we use the [INAUDIBLE] for this. Remember, in week two, if you used soft [INAUDIBLE] flow and got an accuracy of around 92%. So let's see if we can do better. We will start with a couple of imports. Again, most of the frameworks are providing the most interesting data sets as imports. So in this case, we will use the end of this data set provided by We will use the already known sequential model type and we import through layer types. Then you already know where it is. So, drop out which is functionality to prevent overfitting is usually only a parameter to a layer but it carries, it moderately as a separate layer. Since deep learning is in any way nothing else than taking functions. This perfectly makes sense. So that during every iteration, a number of random neurons get frozen and deviate an update. So this prevents over-fitting, and that model generalizes better. Is a layer that reduces the dimensionality of a which we will see later. The initial lectures series on this topic can find in the below links: Introduction to Anomaly Detection https://www.youtube.com/watch?v=IFHX4HUAo1w&list=PLpW3QouFxOnM6YWVOrcUBaQiy8EWi05pi&index=37

How to implement an anomaly detector (1/2) https://www.youtube.com/watch?v=DN0H2Qz3Rxg How to implement an anomaly detector (2/2) https://www.youtube.com/watch?v=nYZuQg5K22Y How to deploy a real-time anomaly detector https://www.youtube.com/watch?v=LnPrT-IkzNw Introduction to Time Series Forecasting https://www.youtube.com/watch?v=G7_uNCOFEzE Stateful vs. Stateless LSTMs https://www.youtube.com/watch?v=R7CwkhZYJdU Batch Size! which batch size is to choose? https://www.youtube.com/watch?v=wfyErdPsZPI Number of Time Steps, Epochs, Training and Validation https://www.youtube.com/watch?v=tsprdX9RkRg Batch size and Trainin Set Size https://www.youtube.com/watch?v=5kLLKhNJlEY Input and Output Data Construction https://www.youtube.com/watch?v=zCHrQRlu688 Designing the LSTM network in Keras https://www.youtube.com/watch?v=Y3ApYArvBr8 Anatomy of a LSTM Node https://www.youtube.com/watch?v=WrA3LlKAbf0 Number of Parameters:How LSTM Parmeter Num is Computed. https://www.youtube.com/watch?v=oXNBR0U1A54 Training and loading a saved model. https://www.youtube.com/watch?v=jKjm1cX-mtM ... https://www.youtube.com/watch?v=o7F_gRekC9Y