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机器学习 is the science of getting computers to learn and act as humans would, and improve their learning over time in an autonomous fashion, 通过以观察和现实世界的互动的形式为它们提供大量的数据. This definition nicely reflects on what are the objectives and aims of this technology.



你有没有试过问机器学习(ML)是什么? The search would result in dozens of academia, researches, forums, articles and interviews. 一个真正的潘多拉魔盒, 主题从“人类的黎明”, or ‘computers will replace human beings’ to ‘the new future’, “技术创造机会”. With the Internet (not to mention other media) and business buzzing about how important it is, 一定有一些超出炒作的东西! 相信十大靠谱网投平台,确实有,十大靠谱网投平台开始吧.

为了简化你的工作, we’re laying out the most important things about 机器学习.


What are the differences between 机器学习 and 人工智能 (AI)

What are the benefits of using 机器学习 solutions

What industries and sectors should be particularly interested in harnessing 机器学习

十大靠谱网投平台将特别关注它的技术方面, 讨论什么框架和库是最常用的,并建议构建可靠的机器学习解决方案


Many tried to encapsulate the essence of 机器学习, 你肯定会在那里找到很多定义. 结果,这只会让事情变得更复杂. So, 让十大靠谱网投平台简单一点:机器学习是一门让计算机像人类一样学习和行动的科学, and improve their learning over time in an autonomous fashion, 通过以观察和现实世界的互动的形式为它们提供大量的数据. This definition nicely reflects on what are the objectives and aims of this technology.


The very name of 机器学习 also tells us its meaning, suggesting it is somehow related to teaching computers to learn. Indeed, ML focuses on training algorithms to make decisions. 用浅显的英语, 有监督学习的ML过程训练模型识别被检查对象属于什么类别. It happens with the use of a classifier with labelled data as an input. 该算法的训练归结为“告诉他”(通过标记)图片上是猫还是狗. Then, the algorithm will analyse next pictures itself, looking for a pattern. Soon, it will be able to classify objects and find cats and dogs on pictures.


In this scenario, it all comes down to the quality of input data. 如果每只狗都被贴上猫的标签, then the algorithm will detect dogs as cats – it’s as simple as that. 这完全取决于十大靠谱网投平台教他什么,他没有完全自学的能力. 此外,交付尽可能多的数据也很重要. The more cases the model is trained with, the more precise its learning will be. 另一方面, 与无监督学习, the algorithms are detecting patterns without labels or input categories. 然后是强化学习, where algorithms learn from observations and environments in order to take particular actions.


Often, 机器学习与人工智能被混淆了,尽管有时会被错误地交替提到, 它们不是一回事. 人工智能的范围肯定更广, is defined as an engineering science of making computers behave human-like. Say, a machine completing a task basing on algorithms making ‘intelligent’ decisions. ML是AI的一部分, focusing on learning computers to act through experience and produce desired outcomes.


现在十大靠谱网投平台知道了机器学习的含义, the next step is to understand what benefits it brings to the business in practical terms. And with growing amounts of data and more powerful computational power and affordable storage, 好处有很多! Here are just 5 most obvious ones, which make ML important for business:


Making the right decisions at the right time is crucial to being successful in business. 随着数据池的不断扩大, 每个组织现在都拥有, 有一种潜在的潜力可以挖掘. ML allows companies to translate data into meaningful information and derive insights, by quickly and automatically produce models that identify opportunities for profits. 在流程和操作中包含这些知识可以将业务提升到一个全新的水平,并有助于保持对风险的控制. 在飞行中,此时此地.

介绍 自动化

Reducing manual tasks plays a vital role in the economy of the 21st century. 与机器学习, businesses can take the most mundane and repetitive tasks off employees, increasing their productivity and allowing them to do more value-adding tasks. 但ML甚至可以帮助完成最复杂的任务, 例如将预测模型应用于实时变化的数据,以支持决策制定.


Effective detecting a breach in network security before its escalation is crucial. In order to increase the overall security of organizations, advanced ML algorithms monitor behavior to detect anomalies in the network. 应用自训练机器学习模型,网络安全水平不断提高, 检测恶意软件, 防止数据泄露或业务中断, 识别网络钓鱼并限制垃圾邮件问题.


使用机器学习, companies can go without a large number of employees focused on doing repetitive work. For example, ML improves time-intensive documentation in data entry. Moreover, 算法有助于简化现有流程,同时也能发现提高性能和削减成本的机会.


机器学习 can also support a business with products – in the way they are designed, 个性化的, 推广和销售. As ML comprehensively consumes incredible amounts of relevant data, 它可以用于数据驱动的营销,以审查和修改关于产品或服务的假设, 包括客户行为和细分, 优化提供和改善个性化,以成功地增加和准确预测终身价值.

机器学习 use cases – who can harness the benefits?

有那么多机器学习的好处, 该技术易于采用和应用
大多数企业已经认识到ML的价值. 自动驾驶汽车,推荐引擎,
healthcare or finance are examples of very important uses of ML in our world today.


防止欺诈和从巨大的数据集中获得见解是机器学习在现代金融和保险领域最流行的两种应用. 这种数据挖掘带来了投资机会, 识别高风险客户, 使用:, performing algorithmic trading operations at speed and scale, 找出欺诈行为或管理投资组合.


机器学习在提高诊断准确性和完善患者治疗方面发挥着重要作用. Algorithms identify risks and recommend medicines, also facilitating recovery. 越来越多的可穿戴物联网设备和传感器产生用于实时评估健康状况的数据. With ML, it’s possible to address medical issues that have been unsolved to date, such as understanding risk factors of diseases in large populations, 治疗糖尿病或癌症.

Recommendation engines, personalisation and online search

Especially in retail, customers expect some sort of personalisation. ML模型的训练基于之前的购买和搜索历史,以创建独特的购物体验, 确定和调整市场营销活动, 优化报价并收集客户洞察. 每当Netflix向你推荐接下来要看什么,或者当谷歌或Facebook用你最近搜索的产品广告攻击你时,机器学习就在发挥作用, analysing your behaviour and comparing it with other users.


多亏了机器学习, smart cars driving autonomously are no longer a science-fiction scenario, 而是十大靠谱网投平台必须适应的现实. A vehicle that communicates with other cars on the road and that learns as it drives (itself, 当然)是一个受欢迎的智慧城市概念. Understanding and analysing data is crucial for the whole transportation industry, making routes more efficient and introducing predictive maintenance features.



ML变得越来越突出,这是毫无疑问的. 随着它越来越受欢迎, 开发人员和科学家可以使用的各种工具和框架不断增多. 在微软这样的大公司的支持下, IBM, AWS或者谷歌, 提供ML api和云服务, 与一系列编码语言相结合, frameworks, 以及与机器学习配合良好的库, 开发人员可以构建
并且可以轻松训练模型. If you expect high-quality results, you should work with these technologies primarily:


说到机器学习和人工智能,Python是最流行和最受欢迎的语言, 原因有很多. 首先,简单的语法是它的一大优点. It resembles everyday English and has a low entry barrier, 因此,许多数据科学家和程序员很快就掌握了它,并且不费多大力气就开始了开发. Secondly, 用Python编写的代码不需要重新编译, 什么使任何更改的实现更快. 更重要的是, 它可以很好地与其他语言配合使用, so developers can make use of other skills they have whilst working in Python. It is also very readable and flexible and allows for combining styles to solve problems. And, 因为它是完全免费和开源的, it has a great community support and lots of resources available to facilitate the work.

But what really makes Python most popular in terms of ML is a great choice of libraries. A library is a module or often a group of published models, 其中包括执行某些特定操作和引入功能的现成代码片段. 和一个图书馆, developers don’t need to code everything from scratch every time, 他们只是使用现成的解决方案, 多么有意义的空闲时间和忙碌. When it comes to Python, it’s libraries are used mostly to access, handle and transform data.


完全用Python编写, Django is probably the most popular open source web framework of this programming language, 用于高级web开发. 它对ML来说很方便,因为它与其他Python库集成,而且非常高效和稳定. Its other perks include multi-site and multi-language support, MVC layout, AJAX支持, free API, URL路由, easy migrations of databases and straightforward session handling. 更重要的是, 由于它的流行,已经有一个很大的Django极客社区提供资源和帮助, 例如在Github上. Django is also a great choice when you have security in mind. 它隐藏了您的web解决方案的源代码, 防止CSRF和XSS攻击, 点击劫持和SQL注入.

机器学习 developers use Django to create a REST application to deploy ML models. 它是一个用于构建web api的工具包, 复杂的模型和算法可以像调用API端点一样轻松部署. 你只是开始了一个项目, 创建Django应用, 编辑一些文件, 创建迁移和超级用户, 然后运行服务器并测试API.


This Python micro-framework for web is made for Python applications, Linkedin或Pinterest等网络达人使用的. Written by Armin Ronacher, it helps with implementing 机器学习 applications in Python. 由于Flask, ML应用可以很容易的插入,扩展和部署为一个“常规”的web应用.

Flask依赖于两个主要的组件:WSGI工具包,它是一个web应用的规范, 和模板引擎Jinja2, 显示网页. 它就像是一组预设的代码包, that can be used as building blocks for a web app and further extended, 在需要的时候. Flask涵盖了广泛的内置功能, 例如上传文件, 对象关系映射, 验证表单, 身份验证或邮件与jquery集成. 因为它是一个非常轻的web框架, Flask also facilitates deployment of 机器学习 models, 训练模型, 保存它并处理API请求.


说到机器学习,高级分析和高级数据结构是至关重要的. 这就是熊猫派上用场的地方, to gather data from external resources (like Excel spreadsheets and CVCs), merge data, 过滤它,然后处理和操纵它. 对许多人来说,它是最好的Python库. 有些人会说, when your dealing with excel datasets and CVCs for 机器学习 and data science, 熊猫是强制性的!

与其他库一样, with Pandas there’s just less writing with more work done, allowing to focus on analysed data rather than code itself. This library significantly streamlines forms of representing data, which helps in understanding patterns and deriving insights. Filtering, 使用Pandas高效地分割或分离甚至大型和复杂的数据集就像一个饼一样简单. 数据的编辑、定制和旋转也是如此.


Data science and 机器学习 is all about math and advanced calculations. 为了在线性代数中有效地进行这种复杂的计算, 开发者需要NumPy这样的数学库. Made especially for Python, NumPy supports complex and multi-dimensional matrices and arrays. It allows for performing logical and mathematical operations and functions on top of them both. 机器学习技术堆栈的真正基础!

这个图书馆用于统计分析, as it consumes noticeably less memory to store the data and is an efficient storage. NumPy使用简单的api, 让机器学习和数据科学的数学计算对开发者来说更容易、更平易近人.


In order to make the data more readable and understandable, 数据科学家使用图表, histograms, 2D图和其他形式的可视化. A Python and NumPy library Matplotlib enables data presentation, 可视化和理解, 也有助于清晰的报告. It’s object-oriented API embeds plots into apps using GUI toolkits.

Matplotlib is efficient and fast-working with many backends and operating systems. 除了不同的图表和直方图, it includes a vast variety of tools to graphically present data in high quality, 例如图或热图, useful depending on the type and amount of data available. Not to mention a large community support, which is always handy!


From the first contact to fully developed and working software, we will share info with you to make sure everything is clear at every stage of the project.

十大靠谱网投平台与他们团队之间的反馈循环在理解十大靠谱网投平台试图完成的任务的过程中是很有帮助的,并且对于交付好的软件是至关重要的. They had an impactful role in lifting our business off the ground. 和他们一起工作很愉快. 他们公司的口号“像兄弟一样工作”是真的. 主人既友好又善解人意.
It’s hard to find an agency with such an optimistic and passionate attitude. 他们的知识给十大靠谱网投平台留下了深刻印象. It was great that we could totally rely on their expertise and skills. 十大靠谱网投平台对ASPER推荐的解决方案和他们管理整个项目的方式非常满意.
Andy creed
他们的主要优势是善于倾听, 所以如果十大靠谱网投平台有问题, ASPER will come back with potential solutions and suggestions. 他们与十大靠谱网投平台合作的方式非常积极主动, 十大靠谱网投平台发现这是整个团队中很有价值的一部分.


When it comes to making the most out of 机器学习, applying appropriate technology by experts with hands-on experience
是非常重要的. 拥有多样化的技术堆栈, 只使用最好的工具, 语言和框架确实可以
enable tapping into the pool of 机器学习 benefits, regardless the industry.

但是,当谈到ML时,还有另一个关键的收获. 数据科学最重要的成功因素和
机器学习就是数据本身. The significance of having adequate amount of high quality data,
structurising it and making it fit for training the algorithms must not be underestimated.
Otherwise, you’ll end up with clutter rather than meaningful insights.


在数据量和复杂性不断扩大的世界中,每个组织都拥有数据, 重要的是要有一个能够充分理解技术的合作伙伴,这样才能充分利用技术.

Asper Brothers is a software house with experience in 机器学习 and data science, 结合特殊, 以积极进取的态度实践专业技术知识. 十大靠谱网投平台了解决策树和神经网络, but also how the business is run and what results it expects.

We know how to translate newest technology into meaningful business results, 这将支持运营和简化流程, bringing your business the insights and predictions you need. 十大靠谱网投平台位于华沙市中心,地理位置优越, a capital of a country with one of the best pool of developers in the world, 还有其他需要考虑的原因吗.

Plus, 十大靠谱网投平台只是一群年轻人, energetic, 友好随和的极客, always eager to support your business goals with technology. We treat both our employees and customers as members of the family, 让你的科技体验更加独特.

Make use of 机器学习 with Asper Brothers and propel your business!




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