应该使用批量学习(batch learning)还是在线学习(online learning)? 如果数据量巨大,可以使用MapReduce技术,将数据分给多个服务器处理。也可是使用在线学习。 2.2.2 选择性能衡量指标(Select a Performance Measure) 回归问题典型的衡量指标选择均方根误差(Root Mean Square Error,RMSE),它揭示了预测值的标准偏差(...
While machine learning does heavily overlap with those fields, it shouldn't be crudely lumped together with them. For example, machine learning isonetool for data science (albeit an essential one). It's alsooneuse of infrastructure that can handle big data. Here are some examples: Supervised ...
Step 2: Discover why Statistical Methods are important for machine learning. The Close Relationship Between Applied Statistics and Machine Learning 10 Examples of How to Use Statistical Methods in a Machine Learning Project Step 3: Dive into the topics of Statistical Methods. ...
1. Understand the business problem and define success criteria.Convert the group's knowledge of the business problem and project objectives into a suitable ML problem definition. Consider why the project requires machine learning, the best type of algorithm for the problem, any requirements for trans...
虽然这个项目并没有使用很复杂的模型,总体难度也不高,但是其代码结构却是我们需要学习的,尤其是要建立这种框架思维,使用这种逻辑分明的结构来生成自己的一套解耦性强的代码,不论是在竞赛还是实验中,都可以非常轻松的进行改动迭代等。 1. Project overview
Regardless of a machine learning project’s scope, its implementation is a time-consuming process consisting of the same basic steps with a defined set of tasks. The distribution of roles in data science teams is optional and may depend on a project scale, budget, time frame, and a specific...
Deepy is an extensible deep learning framework based on Theano. It provides a clean, high-level interface for components such as LSTMs, Batch Normalization, and Auto Encoders. Deepy clearly aims for simplicity, and itsdocumentationand examples aim for the same. It also has a sister project,...
从总体上来说,一个Machine Learning Project Checklist可以分为下面8个大步骤(文末我给出了整个步骤的具体思维导图): 1. Frame the problem and look at the big picture 2. Get the data. 3. Explore the data to gain insights 4. Prepare the data to better expose the underlying data patterns to Ma...
【】A learning algorithm’s performance can never be better than human-level performance but it can be better than Bayes error. (学习算法的性能不可能优于人类表现,但它可以优于贝叶斯 错误的基准线。) 【】A learning algorithm’s performance can never be better than human-level performance nor bett...
An epoch in machine learning refers to one complete pass of the training dataset through a neural network, helping to improve its accuracy and performance.