Blog / News
- Level-Up This November with the ODSC West 2021 Keynotes and Training Sessions, by ODSC [Prod] - Oct 20, 2021.
At ODSC West 2021 this November 16th-18th, we’ll have 80+ training sessions and workshops on essential tools and languages led by some of the best and brightest minds in data science and AI.
- Data Preparation in R using dplyr, with Cheat Sheet!, by Stan Pugsley [Tuto] - Oct 20, 2021.
Leverage the powerful data wrangling tools in R’s dplyr to clean and prepare your data.
- Data Science Portfolio Project Ideas That Can Get You Hired (Or Not), by Nate Rosidi [Tuto] - Oct 20, 2021.
Choosing what to include in your data science portfolio during the job search is the most important part of the process. Each project should be well-structured so that a hiring manager can assess your skills quickly. To help you get started, we highlight a few data science project ideas that you should consider for your portfolio.
- Data Scientist vs Data Engineer Salary, by Matthew Przybyla [Opin] - Oct 20, 2021.
What are the differences between these two popular tech roles?
- KDnuggets™ News 21:n40, Oct 20: The 20 Python Packages You Need For Machine Learning and Data Science; Ace Data Science Interviews with Portfolio Projects, by KDnuggets - Oct 20, 2021.
The 20 Python Packages You Need For Machine Learning and Data Science; How to Ace Data Science Interview by Working on Portfolio Projects; Deploying Your First Machine Learning API; Real Time Image Segmentation Using 5 Lines of Code; What is Clustering and How Does it Work?
- 2021 Data Engineer Salary Report Shares Insights on a Swiftly Evolving Market, by Burtch Works [Prod] - Oct 19, 2021.
Over the past few years, the data engineering market has seen tremendous growth. The acceleration of the data engineering market prompted us to create a new report specifically for data engineering professionals. You can download both the 2021 Data Engineering and 2021 Data Science & Analytics salary reports from our website for free.
- How Data Professionals Can Impress Even When Busy, by Devin Partida [Opin] - Oct 19, 2021.
While there may be plenty of room for advancement even when busy, how to achieve that isn’t always clear. In that spirit, here are five ways you can impress your company leadership.
- 11 Most Practical Data Science Skills for 2022, by Terence Shin [Tuto] - Oct 19, 2021.
While the field of data science continues to evolve with exciting new progress in analytical approaches and machine learning, there remain a core set of skills that are foundational for all general practitioners and specialists, especially those who want to be employable with full-stack capabilities.
- How to Create an Interactive Dashboard in Three Steps with KNIME Analytics Platform, by Emilio Silvestri [Tuto] - Oct 19, 2021.
In this blog post I will show you how to build a simple, but useful and good-looking dashboard to present your data - in three simple steps!
- Top Stories, Oct 11-17: Query Your Pandas DataFrames with SQL, by KDnuggets [Top ] - Oct 18, 2021.
Also: How to Ace Data Science Interview by Working on Portfolio Projects; AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch; How to Build Strong Data Science Portfolio as a Beginner; 8 Must-Have Git Commands for Data Scientists
- Knowledge Graph Forum: Technology Ecosystem and Business Applications, by Ontotext [Prod] - Oct 18, 2021.
Ontotext is thrilled to invite you to the Ontotext & partners virtual Knowledge Graph Forum, Oct 26 & 27, 2021. This event is shaped by Ontotext’s vision that knowledge graphs serve as a hub for data, metadata and content. 35+ speakers from around the globe will share their experiences through real-life cases and platforms demonstrations. Save your spot now.
- Real Time Image Segmentation Using 5 Lines of Code, by Ayoola Olafenwa [Tuto] - Oct 18, 2021.
PixelLib Library is a library created to allow easy integration of object segmentation in images and videos using few lines of python code. PixelLib now provides support for PyTorch backend to perform faster, more accurate segmentation and extraction of objects in images and videos using PointRend segmentation architecture.
- Avoid These Five Behaviors That Make You Look Like A Data Novice, by Tessa Xie [Opin] - Oct 18, 2021.
If you are new to the Data Science industry or a well-versed veteran in all things data and analytics, there are always key pitfalls that each of us can easily slide into if we are not careful. These behaviors not only make us appear like novices, but they can risk our position as a trustworthy, likable data partner with stakeholder.
- Serving ML Models in Production: Common Patterns, by Mo, Oakes & Galarnyk [Tuto] - Oct 18, 2021.
Over the past couple years, we've seen 4 common patterns of machine learning in production: pipeline, ensemble, business logic, and online learning. In the ML serving space, implementing these patterns typically involves a tradeoff between ease of development and production readiness. Ray Serve was built to support these patterns by being both easy to develop and production ready.
- KDnuggets Top Blogs Rewards for September 2021, by Gregory Piatetsky [Top ] - Oct 15, 2021.
The September blogs that earned KDnuggets Rewards include: Do You Read Excel Files with Python? There is a 1000x Faster Way; Data Scientists Without Data Engineering Skills Will Face the Harsh Truth; Path to Full Stack Data Science; Nine Tools I Wish I Mastered Before My PhD in Machine Learning
- Learn from Northwestern Data Science experts, by Northwestern [Prod] - Oct 15, 2021.
Build the essential technical, analytical, and leadership skills needed for careers in today's data-driven world in Northwestern’s Master of Science in Data Science program. Apply now.
- How our Obsession with Algorithms Broke Computer Vision: And how Synthetic Computer Vision can fix it, by Paul Pop [Opin] - Oct 15, 2021.
Deep Learning radically improved Machine Learning as a whole. The Data-Centric revolution is about to do the same. In this post, we’ll take a look at the pitfalls of mainstream Computer Vision (CV) and discuss why Synthetic Computer Vision (SCV) is the future.
- New Computing Paradigm for AI: Processing-in-Memory (PIM) Architecture, by Nam Sung Kim [Tuto] - Oct 15, 2021.
As larger deep neural networks are trained on the latest and fastest chip technologies, an important challenge remains that bottlenecks performance -- and it is not compute power. You can try to calculate a DNN as fast as possible, but there is data -- and it has to move. Data pipelines on the chip are expensive and new solutions must be developed to advance capabilities.
- How to calculate confidence intervals for performance metrics in Machine Learning using an automatic bootstrap method, by David B Rosen (PhD) [Tuto] - Oct 15, 2021.
Are your model performance measurements very precise due to a “large” test set, or very uncertain due to a “small” or imbalanced test set?
- Amazon Web Services Webinar: Leverage data sets to create a customer-centric strategy and improve business outcomes, by Roidna [Prod] - Oct 14, 2021.
Register now for this webinar, Oct 28, to learn how using third-party data enhances applications to better prioritize your target customer - helping you build a more customer-centric business.
- Deploying Your First Machine Learning API, by Abid Ali Awan [Tuto] - Oct 14, 2021.
Effortless way to develop and deploy your machine learning API using FastAPI and Deta.
- The 20 Python Packages You Need For Machine Learning and Data Science, by Sandro Luck [Tuto] - Oct 14, 2021.
Do you do Python? Do you do data science and machine learning? Then, you need to do these crucial Python libraries that enable nearly all you will want to do.
- What is Clustering and How Does it Work?, by Satoru Hayasaka [Tuto] - Oct 14, 2021.
Let us examine how clusters with different properties are produced by different clustering algorithms. In particular, we give an overview of three clustering methods: k-Means clustering, hierarchical clustering, and DBSCAN.
- How Hasura Improved Conversion Rates By 20% With PostHog, by PostHog [Prod] - Oct 13, 2021.
Find out how Hasura increased conversion rates by 10-20% by using PostHog for self-hosted product analytics!
- Will Your Job be Replaced by a Machine?, by Martin Perry [Opin] - Oct 13, 2021.
Yes! It will happen. However, you can pivot and thrive in this disruptive time by becoming a Citizen Developer!
- How to Ace Data Science Interview by Working on Portfolio Projects, by Abid Ali Awan [Tuto] - Oct 13, 2021.
Recruiters of Data Science professionals around the world focus on portfolio projects rather than resumes and LinkedIn profiles. So, learning early how to contribute and share your work on GitHub, Deepnote, and Kaggle can help you perform your best during data science interviews.
- Building Multimodal Models: Using the widedeep Pytorch package, by Rajiv Shah [Tuto] - Oct 13, 2021.
This article gets you started on the open-source widedeep PyTorch framework developed by Javier Rodriguez Zaurin.
- KDnuggets™ News 21:n39, Oct 13: 8 Must-Have Git Commands for Data Scientists; 38 Free Courses on Coursera for Data Science, by KDnuggets - Oct 13, 2021.
The 8 Git commands Data Scientists should know; 38 free courses on Coursera for Data Science; How to query your Pandas DataFrames with SQL; Why You Need Python Skills as a Machine Learning Engineer; and more.
- Top September Stories: Do You Read Excel Files with Python? There is a 1000x Faster Way, by KDnuggets [Top ] - Oct 12, 2021.
Also: Data Scientists Without Data Engineering Skills Will Face the Harsh Truth; Nine Tools I Wish I Mastered Before My PhD in ML; A Data Science Portfolio That Will Land You The Job
- Transforming your business with SAS® Viya® on Microsoft Azure, by SAS [Prod] - Oct 12, 2021.
Faster, trusted decisions are in the cloud. See how you can use the flexibility, scalability and agility of modern technologies to advance your organization’s goals. Read our blog with 3-part video demo.
- Create Synthetic Time-series with Anomaly Signatures in Python, by Tirthajyoti Sarkar [Tuto] - Oct 12, 2021.
A simple and intuitive way to create synthetic (artificial) time-series data with customized anomalies — particularly suited to industrial applications.
- How I Built A Perfect Model And Got Into Trouble, by Oleg Novikov [Opin] - Oct 12, 2021.
Data-driven decisions, actionable insights, business impact—you've seen these buzzwords in data science jobs descriptions. But, just focusing on these terms doesn't automatically lead to the best results. Learn from this real-world scenario that followed data-driven indecisiveness, found misleading insights, and initially created a negative business impact.
- Step by Step Building a Vacancy Tracker Using Tableau, by Dotun Opasina [Tuto] - Oct 12, 2021.
Step-by-step explanations of vacancies valued in tens of millions of dollars in the small town of Fitchburg, Massachusetts.
- PASS Data Community Summit – Free Online Conference for Data Professionals, by PASS [Prod] - Oct 11, 2021.
PASS Data Community Summit 2021 is the year’s largest gathering of Microsoft data platform professionals. This FREE online conference (taking place November 8 – 12, 2021) features 200+ world-class speakers and sessions, and gives you the opportunity to connect, share, and learn with thousands of your peers from the global data platform community.
- Top Stories, Oct 4-10: How to Build Strong Data Science Portfolio as a Beginner; 38 Free Courses on Coursera for Data Science, by KDnuggets [Top ] - Oct 11, 2021.
Also: Data science SQL interview questions from top tech firms; Here’s Why You Need Python Skills as a Machine Learning Engineer; 8 Must-Have Git Commands for Data Scientists; Introduction to PyTorch Lightning
- AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch, by Kevin Vu [Tuto] - Oct 11, 2021.
AutoML is a broad category of techniques and tools for applying automated search to your automated search and learning to your learning. In addition to Auto-Sklearn, the Freiburg-Hannover AutoML group has also developed an Auto-PyTorch library. We’ll use both of these as our entry point into AutoML in the following simple tutorial.
- Scaling human oversight of AI systems for difficult tasks – OpenAI approach, by OpenAI [Tuto] - Oct 11, 2021.
The foundational idea of Artificial Intelligence is that it should demonstrate human-level intelligence. So, unless a model can perform as a human might do, its intended purpose is missed. Here, recent OpenAI research into full-length book summarization focuses on generating results that make sense to humans with state-of-the-art results that leverage scalable AI-enhanced human-in-the-loop feedback.
- Query Your Pandas DataFrames with SQL, by Matthew Mayo [Tuto] - Oct 11, 2021.
Learn how to query your Pandas DataFrames using the standard SQL SELECT statement, seamlessly from within your Python code.
- Choose The Right Job in Data: 5 Signs To Look For In An Engineering Culture, by Niv Sluzki [Opin] - Oct 8, 2021.
Software engineers seeking jobs at data companies face a new problem: choosing the right job out of all the options. Learn the 5 signs that signal an agile and innovative engineering culture.
- Are you familiar with data labeling?, by Toloka [Prod] - Oct 8, 2021.
Are you familiar with common data labeling approaches and tools? Take a simple 2-minute survey.
- 8 Must-Have Git Commands for Data Scientists, by Soner Yildirim [Tuto] - Oct 8, 2021.
Git is a must-have skill for data scientists. Maintaining your development work within a version control system is absolutely necessary to have a collaborative and productive working environment with your colleagues. This guide will quickly start you off in the right direction for contributing to an existing project at your organization.
- Dealing with Data Leakage, by Susan Currie Sivek, Ph.D. [Tuto] - Oct 8, 2021.
Target leakage and data leakage represent challenging problems in machine learning. Be prepared to recognize and avoid these potentially messy problems.
- Transforming the Shop Floor: A No-BS Look at Data Science in Manufacturing, by RapidMiner [Prod] - Oct 7, 2021.
Join RapidMiner live on LinkedIn, Oct 28, to learn how you can lead a digital transformation—not by starting from scratch, but by getting more from what you already have. We’ll walk through a series of real-world examples to demonstrate how your data, when paired with machine learning, can be used to make smarter process decisions.
- The Evolution of Tokenization – Byte Pair Encoding in NLP, by Harshit Tyagi [Tuto] - Oct 7, 2021.
Though we have SOTA algorithms for tokenization, it's always a good practice to understand the evolution trail and learning how have we reached here. Read this introduction to Byte Pair Encoding.
- Building and Operationalizing Machine Learning Models: Three tips for success, by Jason Revelle [Opin] - Oct 7, 2021.
With more enterprises implementing machine learning to improve revenue and operations, properly operationalizing the ML lifecycle in a holistic way is crucial for data teams to make their projects efficient and effective.
- How to do “Limitless” Math in Python, by Tirthajyoti Sarkar [Tuto] - Oct 7, 2021.
How to perform arbitrary-precision computation and much more math (and fast too) than what is possible with the built-in math library in Python.
- Here’s Why You Need Python Skills as a Machine Learning Engineer, by UCSD [Prod] - Oct 6, 2021.
If you want to learn how to apply Python programming skills in the context of AI applications, the UC San Diego Extension Machine Learning Engineering Bootcamp can help. Read on to find out more about how machine learning engineers use Python, and why the language dominates today’s machine learning landscape.
- Four Different Pipes for R with magrittr, by Gregory Janesch [Tuto] - Oct 6, 2021.
The magrittr package supplies the pipe operator (%>%), but it turns out that the package actually contains four pipe operators in total. Let's go into them a bit.
- 38 Free Courses on Coursera for Data Science, by Aqsa Zafar [Tuto] - Oct 6, 2021.
There are so many online resources for learning data science, and a great deal of it can be used at no cost. This collection of free courses hosted by Coursera will help you enhance your data science and machine learning skills, no matter your current level of expertise.
- My AI Plays Piano for Me, by Kathrin Melcher [Tuto] - Oct 6, 2021.
Training an RNN with a Combined Loss Function.
- KDnuggets™ News 21:n38, Oct 6: Build a Strong Data Science Portfolio; Surpassing Trillion Parameters with Switch Transformers — a path to AGI?, by KDnuggets - Oct 6, 2021.
How to Build Strong Data Science Portfolio as a Beginner; Surpassing Trillion Parameters and GPT-3 with Switch Transformers — a path to AGI?; How Deep Is That Data Lake?; Data Science Process Lifecycle; Use These Unique Data Sets to Sharpen Your Data Science Skills; How to Auto-Detect the Date/Datetime Columns and Set Their Datatype When Reading a CSV File in Pandas
- Eight Data Science Specializations, and Why You Should Pick One, by Pace University [Prod] - Oct 5, 2021.
With so many Data Science specializations, where should you focus? The Pace University online Master of Science in Data Science features elective courses which allow you to focus on topics that suit your career path so that you can begin to develop a unique specialization.
- Will Data Analysts be Replaced by AI?, by Ngwa Bandolo Bobga Cyril [Opin] - Oct 5, 2021.
It's the question so many are asking: will data analysts be replaced by AI? Read this well-reasoned and concise opinion by someone with insight into the matter.
- Data science SQL interview questions from top tech firms, by Nate Rosidi [Tuto] - Oct 5, 2021.
As a data scientist, there is one thing you really need to understand and know how to handle: data. With SQL being a foundational technical approach for working with data, it should not be surprising that the top tech companies will ask about your SQL skills during an interview. Here, we cover the key concepts tested so you can best prepare for your next data science interview.
- The Architecture Behind DeepMind’s Model for Near Real Time Weather Forecasts, by Jesus Rodriguez [Tuto] - Oct 5, 2021.
Deep Generative Model of Rain (DGMR) is the newest creation from DeepMind which can predict precipitation in short term intervals.
- Top Stories, Sep 27 – Oct 3: Path to Full Stack Data Science, by KDnuggets [Top ] - Oct 4, 2021.
Also: How To Build A Database Using Python; Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?; Nine Tools I Wish I Mastered Before My PhD in Machine Learning; 20 Machine Learning Projects That Will Get You Hired
- Parallelizing Python Code, by Borycki & Galarnyk [Tuto] - Oct 4, 2021.
This article reviews some common options for parallelizing Python code, including process-based parallelism, specialized libraries, ipython parallel, and Ray.
- How to Build Strong Data Science Portfolio as a Beginner, by Abid Ali Awan [Tuto] - Oct 4, 2021.
After learning the basics of data science, you can start to work on real-world problems. But how do you showcase your work? In this article, we are going to learn a unique way to create a data science portfolio.
- Introduction to PyTorch Lightning, by Kevin Vu [Tuto] - Oct 4, 2021.
PyTorch Lightning is a high-level programming layer built on top of PyTorch. It makes building and training models faster, easier, and more reliable.
- Cartoon: How Deep Is That Data Lake?, by Gregory Piatetsky [Opin] - Oct 2, 2021.
New KDnuggets Cartoon looks at some of the problems data engineers may encounter when trying to measure data lakes.
- Teaching AI to Classify Time-series Patterns with Synthetic Data, by Tirthajyoti Sarkar [Tuto] - Oct 1, 2021.
How to build and train an AI model to identify various common anomaly patterns in time-series data.
- Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?, by Kevin Vu [Opin] - Oct 1, 2021.
Ever larger models churning on increasingly faster machines suggest a potential path toward smarter AI, such as with the massive GPT-3 language model. However, new, more lean, approaches are being conceived and explored that may rival these super-models, which could lead to a future with more efficient implementations of advanced AI-driven systems.
- How to Auto-Detect the Date/Datetime Columns and Set Their Datatype When Reading a CSV File in Pandas, by David B Rosen (PhD) [Tuto] - Oct 1, 2021.
When read_csv( ) reads e.g. “2021-03-04” and “2021-03-04 21:37:01.123” as mere “object” datatypes, often you can simply auto-convert them all at once to true datetime datatypes.
- How to Determine the Best Fitting Data Distribution Using Python, by Matthew Mayo [Tuto] - Sep 30, 2021.
Approaches to data sampling, modeling, and analysis can vary based on the distribution of your data, and so determining the best fit theoretical distribution can be an essential step in your data exploration process.
- Scale and Govern AI Initiatives with ModelOps, by Giuliano Liguori [Opin] - Sep 30, 2021.
AI/ML model life cycle automation and orchestration ensures reliable model operations and governance at scale. The path to production for each enterprise model can vary, along with different monitoring, continuous improvement, retirement needs. Organizations must now consider ModelOps as a fundamental capability towards operational excellence and immediate ROIs.
- Advanced Statistical Concepts in Data Science, by Nagesh Singh Chauhan [Tuto] - Sep 30, 2021.
The article contains some of the most commonly used advanced statistical concepts along with their Python implementation.
- Use These Unique Data Sets to Sharpen Your Data Science Skills, by U. of North Florida [Tuto] - Sep 29, 2021.
Want to get your hands on some real-world data sets right now? Kick off your bootcamp prep with this list of hot-button data sets curated to help you hone different data science skills.
- GitHub Desktop for Data Scientists, by Drew Seewald [Tuto] - Sep 29, 2021.
Less scary than version control in the command line.
- Important Statistics Data Scientists Need to Know, by Lekshmi Sunil [Tuto] - Sep 29, 2021.
Several fundamental statistical concepts must be well appreciated by every data scientist -- from the enthusiast to the professional. Here, we provide code snippets in Python to increase understanding to bring you key tools that bring early insight into your data.
- Data Science Process Lifecycle, by Lillian Pierson, P.E. [Opin] - Sep 29, 2021.
How would it feel to know that without a doubt, the data projects you were working on would create TRUE ROI for your organization? Stick around until the end to get my data science process lifecycle framework so that each data project you run is a smashing success.
- KDnuggets™ News 21:n37, Sep 29: Nine Tools I Wish I Mastered Before My PhD in Machine Learning; Path to Full Stack Data Science, by KDnuggets - Sep 29, 2021.
Whether you have a PhD or not, learn these very useful 9 tools to increase your mastery of Machine Learning; Check this detailed path to becoming a full stack Data Scientist; Then do one of these 20 Machine Learning Projects that will help you get a job; See a Breakdown of Deep Learning Frameworks; and more.
- Transform speech into knowledge with Huggingface/Facebook AI and expert.ai, by Expert.ai [Prod] - Sep 28, 2021.
Speech2Data is a blend of open source and free-to-use AI models and technologies powered by Huggingface, Facebook AI and expert.ai. Learn more here.
- How To Build A Database Using Python, by Irfan Alghani Khalid [Tuto] - Sep 28, 2021.
Implement your database without handling the SQL using the Flask-SQLAlchemy library.
- MLOps and ModelOps: What’s the Difference and Why it Matters, by Stu Bailey [Opin] - Sep 28, 2021.
These two terms are often used interchangeably. However, there are key distinctions between the functionality and features each provide, and the AI value and scalability at your organization depend on them.
- Building a Structured Financial Newsfeed Using Python, SpaCy and Streamlit, by Harshit Tyagi [Tuto] - Sep 28, 2021.
Getting started with NLP by building a Named Entity Recognition(NER) application.
- Top Stories, Sep 20-26: Nine Tools I Wish I Mastered Before My PhD in Machine Learning; How to Find Weaknesses in your Machine Learning Models, by KDnuggets [Top ] - Sep 27, 2021.
Also: How to be a Data Scientist without a STEM degree; Data Scientists Without Data Engineering Skills Will Face the Harsh Truth; 20 Machine Learning Projects That Will Get You Hired; How to Find Weaknesses in your Machine Learning Models
- Computer Vision in Agriculture, by Kevin Vu [Tuto] - Sep 27, 2021.
Deep learning isn’t just for placing ads or identifying cats anymore. Instead, a slew of young startups have started to incorporate the advances in computer vision made possible through larger and larger neural networks to real working robots in the fields.
- Path to Full Stack Data Science, by Jawwad Siddique [Tuto] - Sep 27, 2021.
Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.
- Zero to RAPIDS in Minutes with NVIDIA GPUs + Saturn Cloud, by Schmitt & Nolis [Tuto] - Sep 27, 2021.
Managing large-scale data science infrastructure presents significant challenges. With Saturn Cloud, managing GPU-based infrastructure is made easier, allowing practitioners and enterprises to focus on solving their business challenges.
- Data Analysis Using Scala, by Roman Zykov [Tuto] - Sep 24, 2021.
It is very important to choose the right tool for data analysis. On the Kaggle forums, where international Data Science competitions are held, people often ask which tool is better. R and Python are at the top of the list. In this article we will tell you about an alternative stack of data analysis technologies, based on Scala.
- Real-Time Histogram Plots on Unbounded Data, by Romain Picard [Tuto] - Sep 24, 2021.
Using histograms on real-time data is not possible in most of the popular data science libraries. In this article you will learn how dynamically compute and display a histogram within a Python notebook.
- How Data Scientists Can Compete in the Global Job Market, by Devin Partida [Opin] - Sep 24, 2021.
Data scientists wanting to stay competitive or break into the field will need the right approach. These techniques will help them search for and secure a new position.
- Introducing PostHog: An open-source product analytics platform, by PostHog [Prod] - Sep 23, 2021.
PostHog is an open-source product analytics platform that helps you and your product team capture, analyze, and make informed decisions based on user behaviour.
- How To Deal With Imbalanced Classification, Without Re-balancing the Data, by David B Rosen (PhD) [Tuto] - Sep 23, 2021.
Before considering oversampling your skewed data, try adjusting your classification decision threshold, in Python.
- A Breakdown of Deep Learning Frameworks, by Kevin Vu [Tuto] - Sep 23, 2021.
Deep Learning continues to evolve as one of the most powerful techniques in the AI toolbox. Many software packages exist today to support the development of models, and we highlight important options available with key qualities and differentiators to help you select the most appropriate for your needs.
- 9 Outstanding Reasons to Learn Python for Finance, by Zulie Rane [Tuto] - Sep 23, 2021.
Is Python good for learning finance and working in the financial world? The answer is not only a resounding YES, but yes for nine very good reasons. This article gets into the details behind why Python is a must-know programming language for anyone who wants to work in the financial sector.
- Messy Data is Beautiful, by SparkBeyond [Prod] - Sep 22, 2021.
Once these types of data have been cleaned, they do more than show organized data sets. They reveal unlimited possibilities, and AI analytics can reveal these possibilities faster and more efficiently than ever before.
- GitHub Copilot and the Rise of AI Language Models in Programming Automation, by Kevin Vu [Tuto] - Sep 22, 2021.
Read on to learn more about what makes Copilot different from previous autocomplete tools (including TabNine), and why this particular tool has been generating so much controversy.
- 20 Machine Learning Projects That Will Get You Hired, by Khushbu Shah [Tuto] - Sep 22, 2021.
If you want to break into the machine learning and data science job market, then you will need to demonstrate the proficiency of your skills, especially if you are self-taught through online courses and bootcamps. A project portfolio is a great way to practice your new craft and offer convincing evidence that an employee should hire you over the competition.
- Nine Tools I Wish I Mastered Before My PhD in Machine Learning, by Aliaksei Mikhailiuk [Opin] - Sep 22, 2021.
Whether you are building a start up or making scientific breakthroughs these tools will bring your ML pipeline to the next level.