怎么样自学人工智能
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(1)<span style="color: black;">认识</span>人工智能的<span style="color: black;">有些</span>背景知识;</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(2)<span style="color: black;">弥补</span>数学或编程知识;</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(3)熟悉<span style="color: black;">设备</span>学习<span style="color: black;">工具</span>库;</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(4)系统的学习AI知识;</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(5)动手去做<span style="color: black;">有些</span>AI应用;</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">1<span style="color: black;">认识</span>人工智能的背景知识</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">人工智能里面的概念<span style="color: black;">非常多</span>,<span style="color: black;">例如</span><span style="color: black;">设备</span>学习、深度学习、神经网络等等,使得初学者觉得人工智能很<span style="color: black;">奥秘</span>,难以理解。刚<span style="color: black;">起始</span>学习的时候,<span style="color: black;">晓得</span>这些名词大致的意思就行了,<span style="color: black;">不消</span>太深究,学习过一段时间,自然<span style="color: black;">亦</span>就清楚这些概念<span style="color: black;">详细</span><span style="color: black;">表率</span>什么了。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">人工智能是交叉学科,其中数学和计算机编程是学习人工智能最<span style="color: black;">要紧</span>的两个方面。这些在“知云AI专栏”之前的<span style="color: black;">文案</span>“认识人工智能”,<span style="color: black;">亦</span>为<span style="color: black;">大众</span>介绍过,没阅读过的<span style="color: black;">朋友</span><span style="color: black;">能够</span>去看一下。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">2<span style="color: black;">弥补</span>数学或编程知识</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">针对</span><span style="color: black;">已然</span>毕业的工程师<span style="color: black;">来讲</span>,在系统学习AI之前,<span style="color: black;">通常</span>要<span style="color: black;">弥补</span><span style="color: black;">有些</span>数学<span style="color: black;">或</span>编程方面的知识。<span style="color: black;">倘若</span>你的数学和编程比较好,<span style="color: black;">那样</span>学习人工智能会<span style="color: black;">容易</span><span style="color: black;">非常多</span>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">非常多</span><span style="color: black;">朋友</span>一<span style="color: black;">说到</span>数学就害怕,<span style="color: black;">不外</span>,学习人工智能,数学<span style="color: black;">能够</span>说是绕<span style="color: black;">不外</span>去的。在入门的<span style="color: black;">周期</span>并不<span style="color: black;">必须</span>太高深的数学,<span style="color: black;">重点</span>是高等数学、线性代数和概率论,<span style="color: black;">亦</span><span style="color: black;">便是</span>说,大一大二学的数学知识<span style="color: black;">已然</span>是完全够用了。<span style="color: black;">倘若</span>想要从事<span style="color: black;">设备</span>学习工程师的工作,<span style="color: black;">或</span>搞人工智能的<span style="color: black;">科研</span>,<span style="color: black;">那样</span>应该多去学习数学知识,数学好将会是工作中的一大<span style="color: black;">优良</span>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Python是在<span style="color: black;">设备</span>学习<span style="color: black;">行业</span>非常受欢迎,<span style="color: black;">能够</span>说是<span style="color: black;">运用</span>最多的一门编程语言,<span style="color: black;">因此呢</span>Python编程<span style="color: black;">亦</span>是<span style="color: black;">必须</span><span style="color: black;">把握</span>的。在众多的编程语言中,Python是比较容易学习和<span style="color: black;">运用</span>的编程语言,学好Python<span style="color: black;">亦</span>会受益<span style="color: black;">非常多</span>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">3熟悉<span style="color: black;">设备</span>学习<span style="color: black;">工具</span>库</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">此刻</span>人们实现人工智能,<span style="color: black;">重点</span>是基于<span style="color: black;">有些</span><span style="color: black;">设备</span>学习的<span style="color: black;">工具</span>库的,<span style="color: black;">例如</span>TensorFlow、PyTorch等等。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在<span style="color: black;">这儿</span><span style="color: black;">举荐</span><span style="color: black;">大众</span>学习PyTorch。PyTorch非常的受欢迎,是容易<span style="color: black;">运用</span>的<span style="color: black;">设备</span>学习<span style="color: black;">工具</span>库,有人<span style="color: black;">这般</span><span style="color: black;">评估</span>PyTorch“<span style="color: black;">亦</span>说不出来怎么好,<span style="color: black;">然则</span><span style="color: black;">运用</span>起来<span style="color: black;">便是</span>很舒服”。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">刚<span style="color: black;">起始</span>学习人工智能的时候,<span style="color: black;">能够</span>先运行一下<span style="color: black;">工具</span>库官网的示例,<span style="color: black;">例如</span>MNIST手写体识别等。<span style="color: black;">这般</span>会对人工智能有一个感性的认识,消除最初的陌生感。<span style="color: black;">而后</span><span style="color: black;">能够</span><span style="color: black;">瞧瞧</span>里面的代码,你会<span style="color: black;">发掘</span>,其实神经网络的程序并不<span style="color: black;">繁杂</span>,<span style="color: black;">然则</span>会对神经网络的原理和训练有<span style="color: black;">非常多</span>的疑问。这是一件好事,<span style="color: black;">由于</span>带着问题去学习,会更有成效。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">4系统的学习人工智能</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">这儿</span>的人工智能<span style="color: black;">重点</span>指<span style="color: black;">设备</span>学习,<span style="color: black;">由于</span><span style="color: black;">日前</span>人工智能<span style="color: black;">重点</span>是<span style="color: black;">经过</span><span style="color: black;">设备</span>学习的方式来实现的。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">设备</span>学习知识<span style="color: black;">重点</span>有三大块:</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(1)传统<span style="color: black;">设备</span>学习算法,<span style="color: black;">例如</span>决策树、随机森林、SVM等,这些<span style="color: black;">叫作</span>作是传统<span style="color: black;">设备</span>学习算法,是相<span style="color: black;">针对</span>深度学习而言的。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(2)深度学习,指的<span style="color: black;">便是</span>深度神经网络,<span style="color: black;">能够</span>说是<span style="color: black;">日前</span>最<span style="color: black;">要紧</span>最核心的人工智能知识。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">(3)强化学习,源于<span style="color: black;">掌控</span>论,有时候<span style="color: black;">亦</span>翻译成<span style="color: black;">加强</span>学习。深度学习<span style="color: black;">能够</span>和强化学习相结合<span style="color: black;">运用</span>,形成深度强化学习。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在<span style="color: black;">这儿</span><span style="color: black;">必须</span><span style="color: black;">晓得</span>的是深度学习并不难学,<span style="color: black;">针对</span><span style="color: black;">有些</span>工科的<span style="color: black;">科研</span>生,<span style="color: black;">通常</span>只<span style="color: black;">必须</span>几周就<span style="color: black;">能够</span>上手,并<span style="color: black;">能够</span>训练<span style="color: black;">有些</span><span style="color: black;">实质</span>应用中的神经网络。<span style="color: black;">然则</span>想要对深入学习有深入理解不是容易的事情,<span style="color: black;">通常</span><span style="color: black;">必须</span>几个月的时间。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">传统<span style="color: black;">设备</span>学习算法的种类非常多,有些算法会有非常多的数学公式,<span style="color: black;">例如</span>SVM等。这些算法并<span style="color: black;">欠好</span>学,<span style="color: black;">因此呢</span><span style="color: black;">能够</span>先学习深度学习,<span style="color: black;">而后</span>再慢慢的<span style="color: black;">弥补</span>这些传统算法。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">强化学习是比较有难度的,<span style="color: black;">通常</span><span style="color: black;">必须</span><span style="color: black;">连续</span>学习两三个月,<span style="color: black;">才可</span>有所领悟。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">5动手去做<span style="color: black;">有些</span>AI应用</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">学习过几周的深度学习之后,就<span style="color: black;">能够</span>动手尝试去做<span style="color: black;">有些</span>AI应用了,<span style="color: black;">例如</span>图像识别,风格迁移,文本诗词生成等等。边实践边学习效果会好<span style="color: black;">非常多</span>,<span style="color: black;">亦</span>会<span style="color: black;">逐步</span>的加深对神经网络的理解。</p>
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