- Deep Learning on your phone: PyTorch C++ API for use on Mobile Platforms - Nov 12, 2021.
The PyTorch Deep Learning framework has a C++ API for use on mobile platforms. This article shows an end-to-end demo of how to write a simple C++ application with Deep Learning capabilities using the PyTorch C++ API such that the same code can be built for use on mobile platforms (both Android and iOS).
- 25 Github Repositories Every Python Developer Should Know - Nov 12, 2021.
Check out these repositories to help you improve your data science skills.
- What Comes After HDF5? Seeking a Data Storage Format for Deep Learning - Nov 9, 2021.
In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data. But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists.
- KDnuggets™ News 21:n42, Nov 3: Google Recommendations Before Taking Their Machine Learning Course; Guide to Data Science Jobs - Nov 3, 2021.
What Google Recommends You do Before Taking Their Machine Learning or Data Science Course; A Guide to 14 Different Data Science Jobs; Analyze Python Code in Jupyter Notebooks; Machine Learning Model Development and Model Operations: Principles and Practices; Want to Join a Bank? Everything Data Scientists Need to Know About Working in Fintech
- ORDAINED: The Python Project Template - Nov 2, 2021.
Recently I decided to take the time to better understand the Python packaging ecosystem and create a project boilerplate template as an improvement over copying a directory tree and doing find and replace.
- Advanced PyTorch Lightning with TorchMetrics and Lightning Flash - Nov 1, 2021.
In this tutorial we will be diving deeper into two additional tools you should be using: TorchMetrics and Lightning Flash. TorchMetrics unsurprisingly provides a modular approach to define and track useful metrics across batches and devices, while Lightning Flash offers a suite of functionality facilitating more efficient transfer learning and data handling, and a recipe book of state-of-the-art approaches to typical deep learning problems.
- Simple Text Scraping, Parsing, and Processing with this Python Library - Oct 29, 2021.
Scraping, parsing, and processing text data from the web can be difficult. But it can also be easy, using Newspaper3k.
- Analyze Python Code in Jupyter Notebooks - Oct 28, 2021.
We present a new tool that integrates modern code analysis techniques with Jupyter notebooks and helps developers find bugs as they write code.
- Getting Started with PyTorch Lightning - Oct 26, 2021.
As a library designed for production research, PyTorch Lightning streamlines hardware support and distributed training as well, and we’ll show how easy it is to move training to a GPU toward the end.
- Introduction to AutoEncoder and Variational AutoEncoder (VAE) - Oct 22, 2021.
Autoencoders and their variants are interesting and powerful artificial neural networks used in unsupervised learning scenarios. Learn how autoencoders perform in their different approaches and how to implement with Keras on the instructional data set of the MNIST digits.
- Find the Best-Matching Distribution for Your Data Effortlessly - Oct 22, 2021.
How to find the best-matching statistical distributions for your data points — in an automated and easy way. And, then how to extend the utility further.
- Training BPE, WordPiece, and Unigram Tokenizers from Scratch using Hugging Face - Oct 21, 2021.
Comparing the tokens generated by SOTA tokenization algorithms using Hugging Face's tokenizers package.
- 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 - 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?
- Real Time Image Segmentation Using 5 Lines of Code - 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.
- Serving ML Models in Production: Common Patterns - 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.
- Deploying Your First Machine Learning API - 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 - 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.
- Building Multimodal Models: Using the widedeep Pytorch package - Oct 13, 2021.
This article gets you started on the open-source widedeep PyTorch framework developed by Javier Rodriguez Zaurin.
- Create Synthetic Time-series with Anomaly Signatures in Python - Oct 12, 2021.
A simple and intuitive way to create synthetic (artificial) time-series data with customized anomalies — particularly suited to industrial applications.
- AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch - 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.
- The Evolution of Tokenization – Byte Pair Encoding in NLP - 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.
- How to do “Limitless” Math in Python - 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 - 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.
- Parallelizing Python Code - Oct 4, 2021.
This article reviews some common options for parallelizing Python code, including process-based parallelism, specialized libraries, ipython parallel, and Ray.
- Teaching AI to Classify Time-series Patterns with Synthetic Data - Oct 1, 2021.
How to build and train an AI model to identify various common anomaly patterns in time-series data.
- How to Auto-Detect the Date/Datetime Columns and Set Their Datatype When Reading a CSV File in Pandas - 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 Build A Database Using Python - Sep 28, 2021.
Implement your database without handling the SQL using the Flask-SQLAlchemy library.
- Building a Structured Financial Newsfeed Using Python, SpaCy and Streamlit - Sep 28, 2021.
Getting started with NLP by building a Named Entity Recognition(NER) application.
- Path to Full Stack Data Science - 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 - 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.
- How To Deal With Imbalanced Classification, Without Re-balancing the Data - Sep 23, 2021.
Before considering oversampling your skewed data, try adjusting your classification decision threshold, in Python.
- 9 Outstanding Reasons to Learn Python for Finance - 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.
- KDnuggets™ News 21:n36, Sep 22: The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python - Sep 22, 2021.
The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python; Introduction to Automated Machine Learning; How to be a Data Scientist without a STEM degree; What Is The Real Difference Between Data Engineers and Data Scientists?
- 15 Must-Know Python String Methods - Sep 21, 2021.
It is not always about numbers.
- If You Can Write Functions, You Can Use Dask - Sep 21, 2021.
This article is the second article of an ongoing series on using Dask in practice. Each article in this series will be simple enough for beginners, but provide useful tips for real work. The first article in the series is about using LocalCluster.
- How to be a Data Scientist without a STEM degree - Sep 20, 2021.
Breaking into data science as a professional does require technical skills, a well-honed knack for problem-solving, and a willingness to swim in oceans of data. Maybe you are coming in as a career change or ready to take a new learning path in life--without having previously earned an advanced degree in a STEM field. Follow these tips to find your way into this high-demand and interesting field.
- Adventures in MLOps with Github Actions, Iterative.ai, Label Studio and NBDEV - Sep 16, 2021.
This article documents the authors' experience building their custom MLOps approach.
- Introduction to Automated Machine Learning - Sep 15, 2021.
AutoML enables developers with limited ML expertise (and coding experience) to train high-quality models specific to their business needs. For this article, we will focus on AutoML systems which cater to everyday business and technology applications.
- How to get Python PCAP Certification: Roadmap, Resources, Tips For Success, Based On My Experience - Sep 15, 2021.
Follow this journey of personal experience -- with useful tips and learning resources -- to help you achieve the PCAP Certification, one of the most reputed Python Certifications, to validate your knowledge against International Standards.
- 5 Must Try Awesome Python Data Visualization Libraries - Sep 15, 2021.
The goal of data visualization is to communicate data or information clearly and effectively to readers. Here are 5 must try awesome Python libraries for helping you do so, with overviews and links to quick start guides for each.
- KDnuggets™ News 21:n35, Sep 15: A Data Science Portfolio That Will Land You The Job; Top 18 Low-Code and No-Code Machine Learning Platforms - Sep 15, 2021.
Here is a Data Science Portfolio that will land you the job; Review the top 18 Low-Code and No-Code Machine Learning platforms; Try these 8 Deep Learning Project Ideas for Beginners; Very useful - working with Python APIs for data science project.
- An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab - Sep 14, 2021.
Get an Introduction to Reinforcement Learning by attempting to balance a virtual CartPole with OpenAI Gym, RLlib, and Google Colab.
- The Prefect Way to Automate & Orchestrate Data Pipelines - Sep 13, 2021.
I am migrating all my ETL work from Airflow to this super-cool framework.
- Working with Python APIs For Data Science Project - Sep 10, 2021.
In this article, we will work with YouTube Python API to collect video statistics from our channel using the requests python library to make an API call and save it as a Pandas DataFrame.
- How to Create an AutoML Pipeline Optimization Sandbox - Sep 9, 2021.
In this article, we will implement an automated machine learning pipeline optimization sandbox web app using Streamlit and TPOT.
- KDnuggets™ News 21:n34, Sep 8: Do You Read Excel Files with Python? There is a 1000x Faster Way; Hypothesis Testing Explained - Sep 8, 2021.
Do You Read Excel Files with Python? There is a 1000x Faster Way; Hypothesis Testing Explained; Data Science Cheat Sheet 2.0; 6 Cool Python Libraries That I Came Across Recently; Best Resources to Learn Natural Language Processing in 2021
- How to Create Stunning Web Apps for your Data Science Projects - Sep 7, 2021.
- Fast AutoML with FLAML + Ray Tune - Sep 6, 2021.
Microsoft Researchers have developed FLAML (Fast Lightweight AutoML) which can now utilize Ray Tune for distributed hyperparameter tuning to scale up FLAML’s resource-efficient & easily parallelizable algorithms across a cluster.
- 6 Cool Python Libraries That I Came Across Recently - Sep 3, 2021.
Check out these awesome Python libraries for Machine Learning.
- Do You Read Excel Files with Python? There is a 1000x Faster Way - Sep 1, 2021.
In this article, I’ll show you five ways to load data in Python. Achieving a speedup of 3 orders of magnitude.
- KDnuggets™ News 21:n33, Sep 1: Top Industries Hiring Data Scientists; The Most Important Tool for Data Engineers - Sep 1, 2021.
The top industries hiring Data Scientists; The most important tool for data engineers (hint - it is not technical); How to Engineer Date Features in Python; 15 Python Snippets to Optimize your Data Science Pipeline
- NLP Insights for the Penguin Café Orchestra - Aug 31, 2021.
We give an example of how to use Expert.ai and Python to investigate favorite music albums.
- CSV Files for Storage? No Thanks. There’s a Better Option - Aug 31, 2021.
Saving data to CSV’s is costing you both money and disk space. It’s time to end it.
- A Python Data Processing Script Template - Aug 31, 2021.
Here's a skeleton general purpose template for getting a Python command line script fleshed out as quickly as possible.
- Introducing Packed BERT for 2x Training Speed-up in Natural Language Processing - Aug 30, 2021.
Check out this new BERT packing algorithm for more efficient training.
- How causal inference lifts augmented analytics beyond flatland - Aug 27, 2021.
In our quest to better understand and predict business outcomes, traditional predictive modeling tends to fall flat. However, causal inference techniques along with business analytics approaches can unravel what truly changes your KPIs.
- 15 Python Snippets to Optimize your Data Science Pipeline - Aug 25, 2021.
Quick Python solutions to help your data science cycle.
- KDnuggets™ News 21:n32, Aug 25: Open Source Datasets for Computer Vision; Django’s 9 Most Common Applications - Aug 25, 2021.
Open Source Datasets for Computer Vision; Django’s 9 Most Common Applications; How to Select an Initial Model for your Data Science Problem; Automate Microsoft Excel and Word Using Python; Stack Overflow Survey Data Science Highlights
- Learning Data Science and Machine Learning: First Steps After The Roadmap - Aug 24, 2021.
Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.
- Django’s 9 Most Common Applications - Aug 23, 2021.
Django is a Python web application framework enjoying widespread adoption in the data science community. But what else can you use Django for? Read this article for 9 use cases where you can put Django to work.
- 5 Things That Make My Job as a Data Scientist Easier - Aug 23, 2021.
After working as a Data Scientist for a year, I am here to share some things I learnt along the way that I feel are helpful and have increased my efficiency. Hopefully some of these tips can help you in your journey :)
- Data Scientist’s Guide to Efficient Coding in Python - Aug 18, 2021.
Read this fantastic collection of tips and tricks the author uses for writing clean code on a day-to-day basis.
- Linear Algebra for Natural Language Processing - Aug 17, 2021.
Learn about representing word semantics in vector space.
- Prefect: How to Write and Schedule Your First ETL Pipeline with Python - Aug 16, 2021.
Workflow management systems made easy — both locally and in the cloud.
- Writing Your First Distributed Python Application with Ray - Aug 16, 2021.
Using Ray, you can take Python code that runs sequentially and transform it into a distributed application with minimal code changes. Read on to find out why you should use Ray, and how to get started.
- How to Train a BERT Model From Scratch - Aug 13, 2021.
Meet BERT’s Italian cousin, FiliBERTo.
- How to Query Your Pandas Dataframe - Aug 9, 2021.
A Data Scientist’s perspective on SQL-like Python functions.
- GPU-Powered Data Science (NOT Deep Learning) with RAPIDS - Aug 2, 2021.
How to utilize the power of your GPU for regular data science and machine learning even if you do not do a lot of deep learning work.
- KDnuggets™ News 21:n28, Jul 28: Design patterns in machine learning; The Best NLP Course is Free - Jul 28, 2021.
What are the Design patterns for Machine Learning and why you should know them? For more advanced readers, how to use Kafka Connect to create an open source data pipeline for processing real-time data; The state-of-the-art NLP course is freely available; Python Data Structures Compared; Update your Machine Learning skills this summer.
- Python Data Structures Compared - Jul 27, 2021.
Let's take a look at 5 different Python data structures and see how they could be used to store data we might be processing in our everyday tasks, as well as the relative memory they use for storage and time they take to create and access.
- Why and how should you learn “Productive Data Science”? - Jul 26, 2021.
What is Productive Data Science and what are some of its components?
- Top Python Data Science Interview Questions - Jul 23, 2021.
Six must-know technical concepts and two types of questions to test them.
- Overview of Albumentations: Open-source library for advanced image augmentations - Jul 22, 2021.
With code snippets on augmentations and integrations with PyTorch and Tensorflow pipelines.
- ColabCode: Deploying Machine Learning Models From Google Colab - Jul 22, 2021.
New to ColabCode? Learn how to use it to start a VS Code Server, Jupyter Lab, or FastAPI.
- Understanding BERT with Hugging Face - Jul 20, 2021.
We don’t really understand something before we implement it ourselves. So in this post, we will implement a Question Answering Neural Network using BERT and a Hugging Face Library.
- How Much Memory is your Machine Learning Code Consuming? - Jul 19, 2021.
Learn how to quickly check the memory footprint of your machine learning function/module with one line of command. Generate a nice report too.
- Top 6 Data Science Online Courses in 2021 - Jul 15, 2021.
As an aspiring data scientist, it is easy to get overwhelmed by the abundance of resources available on the Internet. With these 6 online courses, you can develop yourself from a novice to experienced in less than a year, and prepare you with the skills necessary to land a job in data science.
- Date Processing and Feature Engineering in Python - Jul 15, 2021.
Have a look at some code to streamline the parsing and processing of dates in Python, including the engineering of some useful and common features.
- KDnuggets™ News 21:n26, Jul 14: Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python; 5 Python Data Processing Tips - Jul 14, 2021.
If Pandas not enough, here are a few good alternatives to processing larger and faster data in Python; 5 Python Data Processing Tips and Code Snippets; Relax! Data Scientists will not go extinct in 10 years, but the role will change; How to Get Practical Data Science Experience to be Career-Ready.
- How to Tell if You Have Trained Your Model with Enough Data - Jul 12, 2021.
WeightWatcher is an open-source, diagnostic tool for evaluating the performance of (pre)-trained and fine-tuned Deep Neural Networks. It is based on state-of-the-art research into Why Deep Learning Works.
- 5 Python Data Processing Tips & Code Snippets - Jul 9, 2021.
This is a small collection of Python code snippets that a beginner might find useful for data processing.
- Pandas not enough? Here are a few good alternatives to processing larger and faster data in Python - Jul 8, 2021.
While the Pandas library remains a crucial workhorse in data processing and management for data science, some limitations exist that can impact efficiencies, especially with very large data sets. Here, a few interesting alternatives to Pandas are introduced to improve your large data handling performance.
- How to Build An Image Classifier in Few Lines of Code with Flash - Jul 7, 2021.
Introducing Flash: The high-level deep learning framework for beginners.
- KDnuggets™ News 21:n25, Jul 7: Data Scientists and ML Engineers Are Luxury Employees; 5 Lessons from McKinsey That Will Make You a Better Data Scientist - Jul 7, 2021.
Are Data Scientists and ML Engineers Luxury Employees? 5 Lessons McKinsey Taught Me That Will Make You a Better Data Scientist; Managing Your Reusable Python Code as a Data Scientist; GitHub Copilot: Your AI pair programmer - what is all the fuss about? and more.
- ROC Curve Explained - Jul 6, 2021.
Learn to visualise a ROC curve in Python.
- Predict Customer Churn (the right way) using PyCaret - Jul 5, 2021.
A step-by-step guide on how to predict customer churn the right way using PyCaret that actually optimizes the business objective and improves ROI.
- From Scratch: Permutation Feature Importance for ML Interpretability - Jun 30, 2021.
Use permutation feature importance to discover which features in your dataset are useful for prediction — implemented from scratch in Python.
- KDnuggets™ News 21:n24, Jun 30: What will the demand for Data Scientists be in 10 years?; Add A New Dimension To Your Photos Using Python - Jun 30, 2021.
What will the demand for Data Scientists be in 10 years? Will Data Scientists be extinct?; Add A New Dimension To Your Photos Using Python; Data Scientists are from Mars and Software Developers are from Venus; How to Train a Joint Entities and Relation Extraction Classifier using BERT Transformer with spaCy 3; In-Warehouse Machine Learning and the Modern Data Science Stack
- Add A New Dimension To Your Photos Using Python - Jun 28, 2021.
Read this to learn how to breathe new life into your photos with a 3D Ken Burns Effect.
- How to Train a Joint Entities and Relation Extraction Classifier using BERT Transformer with spaCy 3 - Jun 28, 2021.
A step-by-step guide on how to train a relation extraction classifier using Transformer and spaCy3.
- Applied Language Technology: A No-Nonsense Approach - Jun 25, 2021.
Here is a free entry-level applied natural language processing course that can fit into any beginner's roadmap to understanding NLP. Check it out.
- How to create an interactive 3D chart and share it easily with anyone - Jun 25, 2021.
This is a short tutorial on a great Plotly feature.
- 10 Python Code Snippets We Should All Know - Jun 24, 2021.
Check out these Python code snippets and start using them to solve everyday problems.
- Workflow Orchestration with Prefect and Coiled - Jun 23, 2021.
Coiled helps data scientists use Python for ambitious problems, scaling to the cloud for computing power, ease, and speed—all tuned for the needs of teams and enterprises. In this demo example, see how to spin up a Coiled cluster to execute Prefect jobs during runtime.
- Create and Deploy Dashboards using Voila and Saturn Cloud - Jun 23, 2021.
Working with and training large datasets, maintaining them all in one place, and deploying them to production is a challenging job. In this article, we covered what Saturn Cloud is and how it can speed up your end-to-end pipeline, how to create dashboards using Voila and Python and publish them to production in just a few easy steps.
- Fine-Tuning Transformer Model for Invoice Recognition - Jun 23, 2021.
The author presents a step-by-step guide from annotation to training.
- KDnuggets™ News 21:n23, Jun 23: Pandas vs SQL: When Data Scientists Should Use Each Tool; How to Land a Data Analytics Job in 6 Months - Jun 23, 2021.
Pandas vs SQL: When Data Scientists Should Use Each Tool; How to Land a Data Analytics Job in 6 Months; A Graph-based Text Similarity Method with Named Entity Information in NLP; The Best Way to Learn Practical NLP?; An introduction to Explainable AI (XAI) and Explainable Boosting Machines (EBM)
- How to troubleshoot memory problems in Python - Jun 21, 2021.
Memory problems are hard to diagnose and fix in Python. This post goes through a step-by-step process for how to pinpoint and fix memory leaks using popular open source python packages.
- Dashboards for Interpreting & Comparing Machine Learning Models - Jun 17, 2021.
This article discusses using Interpret to create dashboards for machine learning models.
- KDnuggets™ News 21:n22, Jun 16: Data Scientists Extinct in 10 Years? Generate Automated PDF Documents with Python - Jun 16, 2021.
Data Scientists be extinct in 10 years? How to generate PDF Documents with Python; Top 10 Data Science Projects for Beginners; Five types of thinking for a high performing data scientist; and how to get interactive plots directly with Pandas.
- Get Interactive Plots Directly With Pandas - Jun 14, 2021.
Telling a story with data is a core function for any Data Scientist, and creating data visualizations that are simultaneously illuminating and appealing can be challenging. This tutorial reviews how to create Plotly and Bokeh plots directly through Pandas plotting syntax, which will help you convert static visualizations into interactive counterparts -- and take your analysis to the next level.
- Building a Knowledge Graph for Job Search Using BERT - Jun 14, 2021.
A guide on how to create knowledge graphs using NER and Relation Extraction.
- How to Generate Automated PDF Documents with Python - Jun 10, 2021.
Discover how to leverage automation to create dazzling PDF documents effortlessly.
- KDnuggets™ News 21:n21, Jun 9: 5 Tasks To Automate With Python; How I Doubled My Income with Data Science and Machine Learning - Jun 9, 2021.
5 Tasks To Automate With Python; How I Doubled My Income with Data Science and Machine Learning; Will There Be a Shortage of Data Science Jobs in the Next 5 Years?; How to Make Python Code Run Incredibly Fast; Stop (and Start) Hiring Data Scientists
- The only Jupyter Notebooks extension you truly need - Jun 8, 2021.
Now you don’t need to restart the kernel after editing the code in your custom imports.
- How to Fine-Tune BERT Transformer with spaCy 3 - Jun 7, 2021.
A step-by-step guide on how to create a knowledge graph using NER and Relation Extraction.
- PyCaret 101: An introduction for beginners - Jun 7, 2021.
This article is a great overview of how to get started with PyCaret for all your machine learning projects.
- Machine Learning Model Interpretation - Jun 2, 2021.
Read this overview of using Skater to build machine learning visualizations.
- How to Create and Deploy a Simple Sentiment Analysis App via API - Jun 1, 2021.
In this article we will create a simple sentiment analysis app using the HuggingFace Transformers library, and deploy it using FastAPI.
- Make Pandas 3 Times Faster with PyPolars - May 31, 2021.
Learn how to speed up your Pandas workflow using the PyPolars library.
- Supercharge Your Machine Learning Experiments with PyCaret and Gradio - May 31, 2021.
A step-by-step tutorial to develop and interact with machine learning pipelines rapidly.
- Topic Modeling with Streamlit - May 26, 2021.
What does it take to create and deploy a topic modeling web application quickly? Read this post to see how the author uses Python NLP packages for topic modeling, Streamlit for the web application framework, and Streamlit Sharing for deployment.
- Write and train your own custom machine learning models using PyCaret - May 25, 2021.
A step-by-step, beginner-friendly tutorial on how to write and train custom machine learning models in PyCaret.
- Building RESTful APIs using Flask - May 21, 2021.
Learn about using the lightweight web framework in Python from this article.
- How to Determine if Your Machine Learning Model is Overtrained - May 20, 2021.
WeightWatcher is based on theoretical research (done injoint with UC Berkeley) into Why Deep Learning Works, based on our Theory of Heavy Tailed Self-Regularization (HT-SR). It uses ideas from Random Matrix Theory (RMT), Statistical Mechanics, and Strongly Correlated Systems.
- Differentiable Programming from Scratch - May 19, 2021.
In this article, we are going to explain what Differentiable Programming is by developing from scratch all the tools needed for this exciting new kind of programming.
- KDnuggets™ News 21:n19, May 19: Vaex: Pandas but 1000x faster; The Most In Demand Skills for Data Engineers in 2021 - May 19, 2021.
Vaex: Pandas but 1000x faster; Best Python Books for Beginners and Advanced Programmers; The Most In Demand Skills for Data Engineers in 2021; The next-generation of AutoML frameworks; and more.
- Animated Bar Chart Races in Python - May 18, 2021.
A quick and step-by-step beginners project to create an animation bar graph for an amazing Covid dataset.
- The Most In Demand Skills for Data Engineers in 2021 - May 18, 2021.
If you are preparing to make a career in data or are looking for opportunities to skill-up in your current data-centric role, then this analysis of in-demand skills for 2021, based on over 17,000 Data Engineer job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
- Easy MLOps with PyCaret + MLflow - May 18, 2021.
A beginner-friendly, step-by-step tutorial on integrating MLOps in your Machine Learning experiments using PyCaret.
- Best Python Books for Beginners and Advanced Programmers - May 14, 2021.
Let's take a look at nine of the best Python books for both beginners and advanced programmers, covering topics such as data science, machine learning, deep learning, NLP, and more.
- Super Charge Python with Pandas on GPUs Using Saturn Cloud - May 12, 2021.
Saturn Cloud is a tool that allows you to have 10 hours of free GPU computing and 3 hours of Dask Cluster computing a month for free. In this tutorial, you will learn how to use these free resources to process data using Pandas on a GPU. The experiments show that Pandas is over 1,000,000% slower on a CPU as compared to running Pandas on a Dask cluster of GPUs.
- KDnuggets™ News 21:n18, May 12: Data Preparation in SQL, with Cheat Sheet!; Rebuilding 7 Python Projects - May 12, 2021.
Data Preparation in SQL, with Cheat Sheet!; Rebuilding My 7 Python Projects; Applying Python’s Explode Function to Pandas DataFrames; Essential Linear Algebra for Data Science and Machine Learning; Similarity Metrics in NLP
- Essential Linear Algebra for Data Science and Machine Learning - May 10, 2021.
Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.
- Ensemble Methods Explained in Plain English: Bagging - May 10, 2021.
Understand the intuition behind bagging with examples in Python.
- Applying Python’s Explode Function to Pandas DataFrames - May 7, 2021.
Read this applied Python method to solve the issue of accessing column by date/ year using the Pandas library and functions lambda(), list(), map() & explode().
- A Comprehensive Guide to Ensemble Learning – Exactly What You Need to Know - May 6, 2021.
This article covers ensemble learning methods, and exactly what you need to know in order to understand and implement them.
- Rebuilding My 7 Python Projects - May 5, 2021.
This is how I rebuilt My Python Projects: Data Science, Web Development & Android Apps.
- How To Generate Meaningful Sentences Using a T5 Transformer - May 3, 2021.
Read this article to see how to develop a text generation API using the T5 transformer.
- XGBoost Explained: DIY XGBoost Library in Less Than 200 Lines of Python - May 3, 2021.
Understand how XGBoost work with a simple 200 lines codes that implement gradient boosting for decision trees.