딥러닝 썸네일형 리스트형 SCPD stanford online SCPD, Stanford Center of Professional Development 1과목 시작했따 xCS234 - Reinforcement Learning 더보기 quiz 1 시나리오 1: 당신은 고객에 대한 정보를 수집하여 표 형식의 데이터세트에 저장하는 프로젝트를 진행하고 있습니다. 프로젝트의 목표는 고객의 갱신 여부를 예측하는 모델을 만드는 것이며, 모델은 계정 담당자가 사용할 수 있도록 해석 가능성이 높아야 합니다. 고객의 갱신 여부를 예측하는 데 적합한 모델 유형은 무엇입니까? Logistic Regression, Neural Network, Decision Trees Since this is a binary classification problem, many machine learning techniques will work for the problem. However, of these three model families, there are really only .. 더보기 apply deep learning or not Deciding when Deep Learning is the Right Tool Deep Learning is a powerful tool, but it's not the only one. In general, the way to choose whether or not to use Deep Learning depends on your task, what kind of data you have, and how complex the relationships in the data are. Scenarios in which to use Deep Learning include but are not limited to: Tasks Binary classification: Deep Learning Logistic .. 더보기 Books to Read and Tools Books to Read We believe that you learn best when you are exposed to multiple perspectives on the same idea. As such, we recommend checking out a few of the books below to get an added perspective on Deep Learning. Grokking Deep Learning by Andrew Trask. Use our exclusive discount code traskud17 for 40% off. This provides a very gentle introduction to Deep Learning and covers the intuition more .. 더보기 Binary Classification Introduction So far in this course, we've learned about how neural networks can solve regression problems. Now we're going to apply neural networks to another common machine learning problem: classification. Most everything we've learned up until now still applies. The main difference is in the loss function we use and in what kind of outputs we want the final layer to produce. Binary Classifica.. 더보기 Dropout and Batch Normalization Introduction There's more to the world of deep learning than just dense layers. There are dozens of kinds of layers you might add to a model. (Try browsing through the Keras docs for a sample!) Some are like dense layers and define connections between neurons, and others can do preprocessing or transformations of other sorts. In this lesson, we'll learn about a two kinds of special layers, not c.. 더보기 Overfitting and Underfitting Introduction Recall from the example in the previous lesson that Keras will keep a history of the training and validation loss over the epochs that it is training the model. In this lesson, we're going to learn how to interpret these learning curves and how we can use them to guide model development. In particular, we'll examine at the learning curves for evidence of underfitting and overfitting.. 더보기 DL, DNN, SGD, https://www.kaggle.com/code/ryanholbrook/a-single-neuron A Single Neuron Explore and run machine learning code with Kaggle Notebooks | Using data from DL Course Data www.kaggle.com Welcome to Deep Learning! Welcome to Kaggle's Introduction to Deep Learning course! You're about to learn all you need to get started building your own deep neural networks. Using Keras and Tensorflow you'll learn how.. 더보기 이전 1 2 3 4 5 6 7 다음
