Finding great mentors are hard to come by these days. With so much information and so many opinions flooding the internet, finding an authority in a specific field can be quite tough.

这些天很难找到优秀的导师。 互联网上充斥着如此众多的信息和众多见解，因此在特定领域寻找权威可能非常困难。

This feat does not devalue the importance of finding mentors in different stages and areas of our lives. Mentorship has long been considered the most effective way to learn and cut your learning curve in half. Heck, there’s even a Bible scripture on it – Proverbs 19:20-NLT “Get all the advice and instruction you can, so you will be wise the rest of your life”.

这一壮举并没有降低在我们生活的不同阶段和领域寻找导师的重要性。 长期以来，导师制一直是学习和将学习曲线减少一半的最有效方法。 哎呀，甚至还有一部圣经经文– 箴言19：20-NLT “ 尽一切可能的建议和指示，这样一生便会很明智 ”。

“If I have seen further it is by standing on the shoulders of Giants” – Isaac Newton

“如果我能进一步看到，那就是站在巨人的肩膀上” –艾萨克·牛顿

With that being said, I thought it necessary to curate a list of effective Data Science professionals that we should all be following, specifically on LinkedIn.

话虽这么说，我认为有必要整理一份我们都应该关注的有效数据科学专业人员的名单，尤其是在LinkedIn上。

Coming up with this list was very difficult and there were so many names I could have added, such as Dat Tran, Kevin Tran, and Steve Nouri to name a few. But I thought “Nah” these names come up so frequently — people should know and be following them by now. I wanted new blood, names that I don’t see thrown about as much but are doing amazing things for the community.

列出此列表非常困难，我可以添加太多名称，例如Dat Tran ， Kevin Tran和Steve Nouri等等。 但是我认为这些名字经常出现“ Nah”(不)，人们现在应该知道并关注它们。 我想要新的血液，虽然我认为名字很少，但是正在为社区做着很棒的事情。

Note: I must also consider that I do not know the whole population of Data Scientist doing amazing work on LinkedIn. If you wish, feel free to comment some names and add their LinkedIn profiles so that we can give them a follow.

注意 ：我还必须考虑，我不知道整个数据科学家在LinkedIn上所做的出色工作。 如果您愿意，请随时评论一些名称并添加其LinkedIn个人资料，以便我们为他们提供关注。

＃1 — Abhishek Thakur (#1 — Abhishek Thakur)

He is the world’s first 4x Kaggle Grandmaster, an Author of one of the most exciting Machine Learning books this year, a Youtuber and Chief Data Scientist at Boost.AI.

他是全球首位4x Kaggle Grandmaster，是今年最激动人心的机器学习书籍之一的作者，还是Boost.AI的Youtuber和首席数据科学家。

If you follow me on LinkedIn, you probably knew that this was coming since I am constantly sharing his post. I personally take tons of inspiration from Abhishek because of how practical he is — everything is applied. I don’t think I’ve ever seen him share something without giving a real world example that is relatable to.

如果您在LinkedIn上关注我，您可能会知道这是即将到来的，因为我一直在分享他的帖子。 我个人从Abhishek那里汲取了很多灵感，因为他的实践能力强-一切都可以运用。 我认为我从未见过他在没有提供与之相关的真实示例的情况下分享某些东西。

Much of his work is definitely targeted towards people with Machine Learning experience, but of late he has been posting many videos surrounding breaking into Data Science — here are some examples:

他的大部分工作肯定是针对具有机器学习经验的人，但最近他发布了许多有关闯入数据科学的视频-以下是一些示例：

• How to Become A Data Scientist in 1 Year (Learn from a Real World Example)

  如何在1年内成为一名数据科学家(从真实示例中学习)

• How do I start My Career In Data Science?

  如何开始我的数据科学职业？

• My Journey: How I Became The World’s First 4x (and 3x) Grand Master on Kaggle

  我的旅程：我如何成为Kaggle上世界上第一个4x(和3x)大师

Disclaimer: His hair changes a lot but I can verify that it is still him!

免责声明 ：他的头发变化很大，但我可以确定它仍然是他！

＃2 — Angshuman Ghosh博士(博士学位，MBA，MBE) (#2 — Dr. Angshuman Ghosh (PhD, MBA, MBE))

Dr. Angshuman shares extremely thought provoking, educational and motivational post surrounding Data Science. I often find myself bookmarking useful resources that he post so I can refer back to it at a later data, for example this 47 page book on Maths For Machine Learning.

昂斯曼(Angshuman)博士在数据科学领域分享了令人发指的启发性，教育性和激励性的文章。 我经常发现自己为他发布的有用资源添加了书签，因此我可以在以后的数据中引用它，例如，这本47页的关于“机器学习的数学”的书。

He was the Lead Data Scientist at Target and is now the Senior Manager at Grab, as well as a Visiting Professor at the Indian Institute of Management. I definitely would advise giving Dr. Angshu a follow and interacting with his post.

他曾是Target的首席数据科学家 ，现在是Grab的高级经理 ，以及印度管理学院的客座教授。 我绝对建议您给Angshu博士一个关注并与他的帖子互动。

Note: For some weird reason Medium does not make a block when I share the Link to his page. Follow Dr. Angshu on LinkedIn

注意 ：由于某些奇怪的原因，当我共享指向他的页面的链接时，Medium没有阻止。 按照医生Angshu上LinkedIn

＃3 — 菲利普·沃尔特 (#3 — Phillip Vollet)

Phillip is a Senior Data Engineer and a radical Natural Language Processing evangelist — I mean literally, radical!

Phillip是一位高级数据工程师，也是一位激进的自然语言处理布道者-我的意思是，太激进了！

He also posts very useful content regarding Data Visualization, Deep Learning and Machine Learning, hence making him an all-rounder to some extent, but in general, he’s definitely going to be talking about NLP.

他还发布了关于数据可视化，深度学习和机器学习的非常有用的内容，因此在某种程度上使他成为多面手，但总的来说，他肯定会谈论NLP。

Give him a follow…

跟着他...

＃4 — 埃里克·韦伯 (#4 — Eric Weber)

I recently started following Eric and since that day it has been non-stop gems on my LinkedIn feed. His post major around advice for Data Professionals, but every so often he will drop a sprinkle of resources that are useful for breaking into the Data field.

我最近开始关注埃里克(Eric)，从那天开始，它一直是我的LinkedIn订阅源中的不停宝石。 他的专业主要是为数据专业人员提供建议，但他经常会浪费大量资源，这些资源对于打入数据领域很有用。

Eric works as the Head of Experimentation and a Data Science Leader at Yelp and I’d definitely put him down as one of the first people to follow.

埃里克(Eric)是Yelp 的实验负责人和数据科学负责人 ，我肯定会把他当成最早跟随他的人之一。

＃5 — 马丹尼 (#5 — Danny Ma)

I feel as though I draw plenty of similarities to Danny so I can relate to his post. Danny is a self-taught Data Scientist and Machine Learning Engineer without a Science, Technology, Engineering or Maths (STEM) degree, Masters or PhD — He even expands on that to say that he has no certifications and struggled to finish 3 online courses. I’m sure many of us can relate.

我觉得自己与Danny有很多相似之处，因此可以参考他的职位。 Danny是一位自学成才的数据科学家和机器学习工程师，没有科学，技术，工程或数学(STEM)学位，硕士学位或博士学位—他甚至在此基础上进一步扩大，说自己没有认证，并且很难完成3项在线课程。 我敢肯定我们很多人都可以联系。

The way Danny breaks down what it is like to work in the field takes away the fright of the massive salaries being attached to roles. Look, I haven’t cooked a meal since I dropped Food Technology in school, but look how talks about the Data Science diet.

丹尼(Danny)打破在野外工作的感觉的方式消除了与角色相关的巨额薪水的恐惧。 看，自从学校放弃食品技术以来，我还没有煮过饭，但请看如何谈论数据科学饮食。

＃6— 凯尔·麦基欧(Kyle McKiou) (#6— Kyle McKiou)

Introducing Kyle is easy — I will just read his headline. I Teach Data Scientist How to Get Jobs, plain and simple. Kyle post when he has something to say and often it’s quite valuable.

介绍Kyle很容易-我会读他的标题。 我教数据科学家如何简单而简单地找到工作。 凯尔(Kyle)在有话要说时发帖，而这通常很有价值。

I know… controversial!

我知道……有争议！

There are various ways to connect with Kyle:

与Kyle建立联系的方式有多种：

• Youtube

  优酷

• Instagram

  Instagram

But this post is about LinkedIn Veterans!

但是这篇文章是关于领英退伍军人的！

＃7 —莱克斯·弗里德曼 (#7 — Lex Fridman)

Lex Fridman is one of a kind, but his posts do remind me that he is truly human — I can prove it because I saw him sweating. He works at MIT doing Research in human-centered AI, Autonomous Vehicles, and Deep Learning.

莱克斯·弗里德曼(Lex Fridman)是其中的一种，但他的帖子确实使我想起他是真正的人-我可以证明这一点，因为我看到他出汗。 他在麻省理工学院工作，从事以人为中心的人工智能，自动驾驶汽车和深度学习的研究。

Ever heard of how Elon Musk manages his time? Well, Elon Musk found enough time (36 minutes to be precise) to sit with the “Russian Hitman” — he said it not me — Oh… I forgot to add, Joe Rogan thought it necessary also.

是否听说过埃隆·马斯克(Elon Musk)如何管理自己的时间？ 好吧，埃隆·马斯克(Elon Musk)找到了足够的时间(准确地说是36分钟)和“俄罗斯杀手”坐在一起-他说不是我-哦……我忘了补充，乔·罗根(Joe Rogan)认为也有必要。

结语 (Wrap Up)

You may be surprised after reading this article but the answer to your question is “YES! There are tons of outstanding Women doing Data Science” and I will be dedicating my next post the 7 women you should be following on LinkedIn — If you’d like to be notified of that post, follow me on Medium.

阅读本文后，您可能会感到惊讶，但问题的答案是“是！ 有大量杰出的女性从事数据科学研究”，我将在下一篇文章中奉献您应该在LinkedIn上关注的7位女性-如果您希望收到有关该职位的通知，请在Medium上关注我。

The list I have provided is in no particular order and is most definitely not the only people in the world doing great stuff in the community. As I’ve mentioned earlier, I want to meet more authorities so if you have some that I haven’t named then definitely link them to me!

我提供的列表没有特别的顺序，并且绝对不是世界上唯一在社区中做得很好的人。 正如我前面提到的，我想遇到更多的权威人士，所以如果您有一些我没有命名的权威人士，那么可以肯定地将它们链接到我身上！

Let’s continue the conversation on LinkedIn…

让我们继续在LinkedIn上进行对话…