Search results for admond lee

Found 17 documents, 13736 searched:

• Here is What I’ve Learned in 2 Years as a Data Scientist

  In this article, for the first time, I’ll consolidate everything that I’ve learned and condense all of these into 5 lessons that I’ve learned in 2 years as a data scientist.

  https://www.kdnuggets.com/2020/09/learned-2-years-data-scientist.html

• Why and How to Use Dask with Big Data

  The Pandas library for Python is a game-changer for data preparation. But, when the data gets big, really big, then your computer needs more help to efficiency handle all that data. Learn more about how to use Dask and follow a demo to scale up your Pandas to work with Big Data.

  https://www.kdnuggets.com/2020/04/dask-big-data.html

• Has AI Come Full Circle? A data science journey, or why I accepted a data science job

  Personal journeys in Data Science can vary greatly between individuals. Some are just getting starting and wading into this vast ocean of opportunity, and others have been involved during its decades-long evolution as a professional field. This review of a longer journey can provide a broader perspective of how you might fit into this interesting career.

  https://www.kdnuggets.com/2020/04/ai-full-circle-data-science-journey.html

• Top February Stories: The Death of Data Scientists – will AutoML replace them?

  Also: Learning from 3 big Data Science career mistakes; Leaders, Changes, and Trends in Gartner 2020 MQ Data Science and Machine Learning Platforms; Why Did I Reject a Data Scientist Job; Free Mathematics Courses for Data Science & Machine Learning.

  https://www.kdnuggets.com/2020/03/top-stories-2020-feb.html

• Top Stories, Feb 10-16: Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist

  Also: Math for Programmers – your guide for solving math problems in code; What Does it Mean to Deploy a Machine Learning Model?; Deep Neural Networks; Easy Image Dataset Augmentation with TensorFlow; Intent Recognition with BERT using Keras and TensorFlow 2

  https://www.kdnuggets.com/2020/02/top-news-week-0210-0216.html

• Why Did I Reject a Data Scientist Job?">Why Did I Reject a Data Scientist Job?

  Snagging that job as a Data Scientist might not be exactly what you were expecting. Consider this advice on carefully considering job titles with what the position might really be like day-to-day.

  https://www.kdnuggets.com/2020/02/why-reject-data-scientist-job.html

• The Essential Toolbox for Data Cleaning

  Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

  https://www.kdnuggets.com/2019/12/essential-toolbox-data-cleaning.html

• Top July Stories: The Death of Big Data and the Emergence of the Multi-Cloud Era

  Also: Top 13 Skills To Become a Rockstar Data Scientist, Top 10 Data Science Leaders You Should Follow; What's wrong with the approach to Data Science?

  https://www.kdnuggets.com/2019/08/top-stories-2019-jul.html

• P-values Explained By Data Scientist

  This article is designed to give you a full picture from constructing a hypothesis testing to understanding p-value and using that to guide our decision making process.

  https://www.kdnuggets.com/2019/07/p-values-explained-data-scientist.html

• Top Stories, Jul 22-28: Top 13 Skills To Become a Rockstar Data Scientist; This New Google Technique Help Us Understand How Neural Networks are Thinking

  Also: Convolutional Neural Networks: A Python Tutorial Using TensorFlow and Keras; Fantastic Four of Data Science Project Preparation; The Death of Big Data and the Emergence of the Multi-Cloud Era; The title CDO started out as a joke

  https://www.kdnuggets.com/2019/07/top-news-week-0722-0728.html

• Top 13 Skills To Become a Rockstar Data Scientist">Top 13 Skills To Become a Rockstar Data Scientist

  Education, coding, SQL, big data platforms, storytelling and more. These are the 13 skills you need to master to become a rockstar data scientist.

  https://www.kdnuggets.com/2019/07/top-13-skills-become-rockstar-data-scientist.html

• Top Stories, Jul 8-14: The Death of Big Data and the Emergence of the Multi-Cloud Era; Training a Neural Network to Write Like Lovecraft

  Also: What's wrong with the approach to Data Science?; Introducing Gen: MITs New Language That Wants to be the TensorFlow of Programmable Inference; Top 10 Data Science Leaders You Should Follow; 5 Probability Distributions Every Data Scientist Should Know; XGBoost and Random Forest with Bayesian Optimisation

  https://www.kdnuggets.com/2019/07/top-news-week-0708-0714.html

• Top 10 Data Science Leaders You Should Follow">Top 10 Data Science Leaders You Should Follow

  If you’re in the data science field, I strongly encourage you to follow these giants— which I’ll list down in the section below — and be a part of our data science community to learn from the best and share your experience and knowledge.

  https://www.kdnuggets.com/2019/07/top-10-data-science-leaders.html

• Top April Stories: The most desired skill in data science; Top 10 Coding Mistakes Made by Data Scientists

  Also: Another 10 Free Must-See Courses for Machine Learning and Data Science; How to Recognize a Good Data Scientist Job From a Bad One.

  https://www.kdnuggets.com/2019/05/top-stories-2019-apr.html

• Top Stories, Apr 22-28: The most desired skill in data science; How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists

  Artificial Intelligence 101 Cheatsheet; AI Supporting The Earth; Data Visualization in Python: Matplotlib vs Seaborn; 2019 Best Masters in Data Science and Analytics Online; Graduating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own

  https://www.kdnuggets.com/2019/04/top-news-week-0422-0428.html

• How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists with Serious Guides">How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists with Serious Guides

  To learn ALL the skills sets in data science is next to impossible as the scope is way too wide. There’ll always be some skills (technical/non-technical) that data scientists don’t know or haven’t learned as different businesses require different skill sets.

  https://www.kdnuggets.com/2019/04/data-science-ultimate-questions-answers-aspiring-data-scientists.html

• Simple Yet Practical Data Cleaning Codes

  Real world data is messy and needs to be cleaned before it can be used for analysis. Industry experts say the data preprocessing step can easily take 70% to 80% of a data scientist's time on a project.

  https://www.kdnuggets.com/2019/02/simple-yet-practical-data-cleaning-codes.html