- Avoid These Mistakes with Time Series Forecasting - Dec 2, 2021.
A few checks to make before training a Machine Learning model on data that could be random.
Forecasting, Mistakes, Python, Time Series
Most Common SQL Mistakes on Data Science Interviews - Nov 23, 2021.
Sure, we all make mistakes -- which can be a bit more painful when we are trying to get hired -- so check out these typical errors applicants make while answering SQL questions during data science interviews.
Interview Questions, Mistakes, SQL
- 5 Data Science Career Mistakes To Avoid - Aug 19, 2021.
Everyone makes mistakes, which can be a good thing when they lead to learning and improvements over time. But, we can also try to first learn from others to expedite our personal growth. To get started, consider these lessons learned the hard way, so you don’t have to.
Career Advice, Data Science, Mistakes
- 5 Mistakes I Wish I Had Avoided in My Data Science Career - Jul 26, 2021.
Everyone makes mistakes, which can be a good thing when they lead to learning and improvements over time. But, we can also try to first learn from others to expedite our personal growth. To get started, consider these lessons learned the hard way, so you don’t have to.
Career Advice, Data Science, Mistakes
- How a Single Mistake Wasted 3 Years of My Data Science Journey - Jun 9, 2021.
Self-paced courses are just sleeping pills; Industry experts are the right choice.
Courses, Data Science, Experts, Mistakes
- 6 Mistakes To Avoid While Training Your Machine Learning Model - Apr 15, 2021.
While training the AI model, multi-stage activities are performed to utilize the training data in the best manner, so that outcomes are satisfying. So, here are the 6 common mistakes you need to understand to make sure your AI model is successful.
Computer Vision, Data Labeling, Machine Learning, Mistakes
- Learning from machine learning mistakes - Mar 19, 2021.
Read this article and discover how to find weak spots of a regression model.
Machine Learning, Mistakes, Modeling, Regression
- 15 common mistakes data scientists make in Python (and how to fix them) - Mar 3, 2021.
Writing Python code that works for your data science project and performs the task you expect is one thing. Ensuring your code is readable by others (including your future self), reproducible, and efficient are entirely different challenges that can be addressed by minimizing common bad practices in your development.
Best Practices, Data Scientist, Jupyter, Mistakes, Programming, Python
- 6 Common Mistakes in Data Science and How To Avoid Them - Sep 10, 2020.
As a novice or seasoned Data Scientist, your work depends on the data, which is rarely perfect. Properly handling the typical issues with data quality and completeness is crucial, and we review how to avoid six of these common scenarios.
Advice, Data Quality, Data Science, Hyperparameter, Mistakes, Overfitting
- Data Scientists think data is their #1 problem. Here’s why they’re wrong. - Sep 4, 2020.
We tend to think it's all about the data. However, for real data science projects at real organizations in real life, there are more fundamental aspects to consider to do data science right.
Business, Data Science, Mistakes, Problem Definition
How (not) to use Machine Learning for time series forecasting: The sequel - Mar 30, 2020.
Developing machine learning predictive models from time series data is an important skill in Data Science. While the time element in the data provides valuable information for your model, it can also lead you down a path that could fool you into something that isn't real. Follow this example to learn how to spot trouble in time series data before it's too late.
Forecasting, Machine Learning, Mistakes, Time Series
- Predicting the President: Two Ways Election Forecasts Are Misunderstood - Mar 27, 2020.
With election cycles always seeming to be in season, predictions on outcomes remain intriguing content for the voting citizens. Misinterpretation of election forecasts also runs rampant, and can impact perceptions of candidates and those who post these predictions. A better fundamental understanding of probability can help improve our collective notion of futurism, and how we monitor elections.
Elections, Forecasting, Mistakes, Politics, Prediction
Top 10 Statistics Mistakes Made by Data Scientists - Jun 7, 2019.
The following are some of the most common statistics mistakes made by data scientists. Check this list often to make sure you are not making any of these while applying statistics to data science.
Data Science, Data Scientist, GitHub, Mistakes, Statistics
How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls - May 10, 2019.
We outline some of the common pitfalls of machine learning for time series forecasting, with a look at time delayed predictions, autocorrelations, stationarity, accuracy metrics, and more.
Forecasting, Machine Learning, Mistakes, Stationarity, Time Series
Top 10 Coding Mistakes Made by Data Scientists - Apr 2, 2019.
Here is a list of 10 common mistakes that a senior data scientist — who is ranked in the top 1% on Stackoverflow for python coding and who works with a lot of (junior) data scientists — frequently sees.
Data Science, Data Scientist, Mistakes, Programming
Common mistakes when carrying out machine learning and data science - Dec 6, 2018.
We examine typical mistakes in Data Science process, including wrong data visualization, incorrect processing of missing values, wrong transformation of categorical variables, and more. Learn what to avoid!
Data Preparation, Data Science, Data Visualization, Machine Learning, Missing Values, Mistakes, Multicollinearity
- Top 6 errors novice machine learning engineers make - Oct 30, 2017.
What common mistakes beginners do when working on machine learning or data science projects? Here we present list of such most common errors.
Beginners, Machine Learning, Mistakes, Outliers, Regression, Regularization, Time Series
- The 5 Common Mistakes That Lead to Bad Data Visualization - Oct 10, 2017.
Here are 5 common mistakes that lead to bad data visualization. Avoid these to get the most out of your data visualizations.
Data Visualization, Mistakes
- How to Lie with Data - Apr 20, 2017.
We expect data scientists to be objective, but intentionally or not, they can produce results that mislead. We examine three common types of “lies” that Data Scientists should be aware of.
Confirmation Bias, Data Visualization, Mistakes, Overfitting
Top mistakes data scientists make when dealing with business people - Apr 13, 2017.
There are no cover articles praising the fails of the many data scientists that don’t live up to the hype. Here we examine 3 typical mistakes and how to avoid them.
Business, Data Scientist, Mistakes, Skills
- Avoid These Common Data Visualization Mistakes - Feb 8, 2016.
Data Visualization is a handy tool which can lead to interesting discoveries about the data, which otherwise wouldn’t have been possible. But, there are common mistakes which could produce the misdirecting results. Learn what are they and how you can avoid them.
Data Visualization, Mistakes
- 7 common mistakes when doing Machine Learning - Mar 7, 2015.
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data. For Big Data, it pays off to analyze the data upfront and then design the modeling pipeline accordingly.
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Machine Learning, Mistakes, Overfitting, Regression, SVM
