Learn how to create and tune a classification model using the LightGBM LightGBMClassifier and tun...
Pandas comes with two functions called truncate() that allow you to crop the top, bottom, or midd...
Learn how to use Spacy to extract nouns and noun phrases from text using the Natural Language Pro...
Learn how to use the Pandas filter() function to filter or subset a dataframe based on the column...
Learn how to use the Pandas filter() function to filter or subset a dataframe based on the column...
Learn how to use the Pandas to_json() function to export a dataframe to JSON, JSON lines, or a ho...
Learn how to use the Pandas query() function to search, filter, or subset a dataframe to show onl...
Learn how to use the Pandas from_records() function to create a dataframe from a list of dictiona...
Learn how to use the Pandas ewm() function with mean() to calculate an exponential moving average...
Learn how to use the Pandas map() function to create a new dataframe column or series based on a ...
The Pandas pipe() function can be used to create data pipelines and works well with the modern Pa...
Learn how to use the Pandas assign() method to create new dataframe columns and avoid the dreaded...
Learn how to time Python code execution in Jupyter notebooks using the timeit magic command built...
Learn how to use pd.__version__ and pd.show_versions() to view the current version of Pandas inst...
Learn how to use the Pandas from_dict() function to create a Pandas dataframe from a Python dicti...
Pandas method chaining is a modern way to improve Pandas code readability and performance by spli...
Learn how to use the Pandas round() function and Numpy ceil() and floor() to round numbers to a g...
Learn how to transpose data and flip the orientation of a Pandas dataframe using the T and transp...
Learn how to use the Pandas to_numeric() function to convert non-numeric strings or objects to nu...
Learn how to use the Pandas set_index() and reset_index() functions to add and remove a single or...
Learn how to use lambda functions in Pandas to run small anonymous custom functions using apply()...
Learn how to measure and reduce memory usage in Pandas using memory_usage(), info(), and categori...
Learn how to calculate the percentage change or percentage difference between two columns in a Pa...
Learn how to get a list of dates for the national holidays or bank holidays of any country using ...
Learn how to use the Spacy EntityRuler for custom Named Entity Recognition, or custom NER, by ext...
Learn to calculate the Spearman's rank correlation coefficient, or Spearman's rho, using the Pand...
Learn how to use perform custom named entity recognition in Pandas with Spacy by analysing the sk...
Learn how to use the Pandas rolling() method to calculate the rolling mean, rolling average, or ...
Learn how to rearrange or reorder columns in Pandas into your desired order using square brackets...
Learn how to use the Pandas split() function to split strings into lists or columns, including th...
Learn how to use the Pandas explode() function to split a list column into multiple rows...
Learn how to use the Pandas std() function to calculate the standard deviation of dataframe colum...
Learn how to use the Pandas sample() function to show a sample of data, including the lesser know...
Learn how to use the Pandas concat() function to concatenate dataframes and add new rows and colu...
Learn how to get and set the values of Pandas dataframe cells using at[] and iat[] methods to ext...
Learn how to use the Pandas pop() method to drop, remove, and extract a column from a dataframe o...
Learn how to select the first and last rows of a Pandas DataFrame using head() and tail(), flip t...
Learn how to use the append() function to add or append rows to a Pandas dataframe or join two da...
Learn how to add a prefix or suffix to Pandas column names and values using add_prefix(), add_suf...
Learn how to find the most common or frequent value in a Pandas dataframe column using value_coun...
Learn how to use the Pandas drop() function to drop dataframe rows and columns based on column na...
Learn to use the Pandas corr() statistical method to compute the Pearson correlation coefficient ...
Learn how to use ABCD classification to classify Google Search Console page data in EcommerceTool...
Learn to use the Pandas date_range() function to create a DatetimeIndex, list, or dataframe of da...
Learn how to slugify column names and values in Pandas by removing non-alphanumeric characters an...
Learn how to identify duplicate Pandas column values and rows using duplicated() and remove or de...
Learn how to use the Pandas unique() and nunique() methods to identify and count unique values in...
Learn how to create a customer retention model (or churn model) in Python using XGBoost and Optun...
Learn how to use the sort_values() and sort_index() methods to sort a Pandas DataFrame by one or ...
Learn how to use the Pandas CategoricalDtype to create custom sort orders for weekdays, month nam...
Learn how to convert a Pandas dataframe, series, or column, to a list or dictionary using the tol...
Learn how to add new columns to a Pandas dataframe using insert, loc, assign, and by manually dec...
Learn to use FunctionTransformer to create a scikit-learn pipeline that includes feature engineer...
Learn how to create a classification model using CatBoostClassifier and tune its hyperparameters ...
Learn how to tune the hyperparameters of an XGBRegressor regression model with Optuna and improve...
Learn how to create an AdaBoost classification model using the scikit-learn AdaBoostClassifier an...
Learn how to zip files and directories with Python using the zipfile module for file compression.
Learn how to list files and directories with Python using the os module, and the listdir(), walk(...
Learn how to use a .gitignore file to keep your repository clean and prevent sensitive informatio...
Learn how to use Spacy for POS tagging in Pandas and identified Parts of Speech, stopwords, and p...
Learn how to convert a Pandas column containing a list of Python dictionaries or JSON objects int...
Learn how to download, transcode, and transcribe YouTube videos with the OpenAI Whisper Automatic...
Learn how to create a Shopify price tracker by scraping a Shopify ecommerce store with Python and...
In this tutorial, we will learn how to create a Quick Response or QR code using Python, the QRCod...
Learn how to use Optuna for XGBoost hyperparameter tuning by tuning model parameters on an XGBCla...
Learn how to use NLTK for Part of Speech tagging in Pandas to analyse the text in a dataframe col...
Learn how to create GitLab issues using Python and the GitLab API, so you can automatically assig...
Learn how to transform Pandas column values into other formats including float, int, datetime, an...
Learn how to use diff() and pct_change() in Pandas to calculate the difference and percentage cha...
Calculating Customer Lifetime Value or CLV is a lot harder to do than most people realise, especi...
Learn how to build a fake review detection model using TfidfVectorizer and a range of machine lea...
The Pandas isna() function is used to check for missing values in dataframe columns. Here's how t...
Learn how to resize images and create thumbnails in Python using Pillow - the Python Imaging Libr...
Learn how to download a YouTube video and transcode it to MP3 using Python and YouTube_DL from wi...
Learn how to change Pandas dataframe settings and options and change the maximum number of rows, ...
Learn how to check Pandas dtypes using info() and cast them to the correct data type using astype...
Learn how to compare Pandas dataframes and individual columns to see if there are any differences...
Pandas is one of the best tools in data science and a great reason to learn Python. Here are 24 P...
Learn how to scrape a Shopify ecommerce site using Python, requests, and the products.json file, ...
Learn how to split or explode a string or Python list stored in a Pandas column into separate col...
Learn how to export data from Pandas dataframes to CSV, TSV, JSON, HTML, Feather, Parquet, Stata,...
The Pandas cut() and qcut() functions are used for data binning, data bucketing, and discretizati...
Multibuy promotions and Buy One, Get One Free or BOGOF deals are widely used in ecommerce. Here's...
Learn how to use GAPandas to measure ecommerce coupon uplift and optimise the AOV of your website...
Learn how to perform custom extraction when web scraping with Advertools using CSS selectors and ...
Learn how to perform web scraping with Advertools in list mode to scrape an XML sitemap and scrap...
Learn how to query the Google Analytics Data API for GA4 using Python with GAPandas4 to fetch you...
Query the Google Analytics Data API using GAPandas4 and get back a full list of dimensions and me...
ABC customer segmentation using the Pareto principle or 80/20 rule to segment customers based on ...
Learn how to rename Pandas dataframe columns, add a prefix or suffix, convert them to lowercase o...
Learn how to scrape a website's internal linking in Python and visualise the connections between ...
Learn how to tokenize text data in Pandas using the NLTK Punkt text tokenizer for Natural Languag...
Learn how to calculate the conversion rate, average order value, and amount of traffic your ecomm...
Learn how to create a Multinomial Naive Bayes text classification model in Python using the sciki...
Learn how to use k-fold cross validation in scikit-learn to create more robust machine learning m...
Learn how to create a random forest classification model using scikit-learn in Python with the sk...
Learn how to create a decision tree classification model using scikit-learn in Python with the sk...
Learn how to dedupe lists in Python using set(), intersection(), and dict.fromkeys() and identify...
Learn how to calculate the number of days between two dates in MySQL using the DATEDIFF() functio...
Learn how to add and subtract from dates in MySQL using the DATE_ADD() and DATE_SUB() functions b...
The CASE statement is used to evaluate a condition and return a value based on the result of the ...
The MySQL DATE_FORMAT() function lets you convert datetime values to other formats. Here's a quic...
SQL string functions and operators allow you to manipulate strings in SQL statements and are very...
The SQL ORDER BY clause is used to sort the results of a SELECT statement so you can place column...
The GROUP BY and HAVING clauses are used to group the results of a SELECT statement and are extre...
Selecting data between two values or dates is easy when you use create a BETWEEN AND expression i...
Learn how to query a MySQL database using SELECT, FROM, WHERE, and AND in simple SQL statements.
Learn how to import a MySQL database onto a MySQL Docker container and query the database using P...
Learn how to read QR codes from images in Python using the OpenCV computer vision library's QRCod...
When creating business reports you'll often need to be able to calculate the month start and mont...
Most ecommerce and marketing teams use ISO week reporting periods. Here's how to calculate ISO we...
Google Trends data can give retailers insight into the growth or decline of searches in the wider...
Python dictionaries allow you to store key-value pairs, so you can store, lookup, and retrieve da...
Learn how to analyse Average Order Value using the Google Analytics API and Jenks natural breaks ...
Learn how to use the Python Requests library to check the status code of a URL and identify wheth...
Google Analytics API query operators let you select or filter specific data from your GA account....
The Google Analytics API does not expose Shopping Behaviour report data such as cart and checkout...
Learn how to use scikit-learn CountVectorizer for n-gram analysis and analyse unigrams, bigrams, ...
Learn how to use try, except, else, and finally (or try catch) for Python exception handling to i...
Learn how to use the Pip Python package manager to install, upgrade, and remove Python packages.
Learn how to calculate the time difference between two dates in Pandas and return the difference ...
The Dropbox API makes it easy to upload, download, share, and delete files using Python and is id...
Learn how to send transactional emails from your Python application using the Mailchimp Transacti...
Learn how to Dockerize your data science application in five minutes so your code runs perfectly ...
Learn how to create an XML feed parser that will read your Google Shopping feed (or any other XML...
Learn how to backup a MySQL database using mysqldump and SSH and download the dump file to your l...
The Pandas apply function lets you apply a function to columns or rows in your Pandas dataframe. ...
The Pandas describe function lets you quickly create descriptive statistics from a dataframe and ...
Learn how to use the Neural Prophet model and EcommerceTools to create time series forecasts of y...
Here are 16 Python web scraping projects you can use on your ecommerce website to improve marketi...
Customer retention rate is one of the most misunderstood marketing metrics. Here's a quick guide ...
Learn how to create a Google rank checker tool using the Python EcommerceTools package so you can...
Learn how to use the Feefo API for ecommerce competitor analysis and understand what products com...
Learn to use EcommerceTools to query the Google Search Console API with Python and compare two ti...
Learn how to create a client secrets JSON key file and set up a Google Service Account so you can...
The RFM model measures Recency, Frequency, and Monetary value and is used to predict future custo...
Learn how to run SEO tests in Python using EcommerceTools to fetch your Google Search Console dat...
Learn how to use the Term-Frequency Inverse Document Frequency (TF IDF) and cosine similarity to ...
Whether you sell magazine subscriptions, mobile phone contracts, broadband, or car insurance, con...
Overfitting reduces model performance. Here's how you can avoid it using the XGBoost early stoppi...
The approaches used for B2B customer segmentation are slightly different from those used in B2C e...
Learn how to use Python to export data from the Google Search Console API using Python and constr...
Improve the efficiency of your customer service team by creating a Naive Bayes model to classify ...
Using pipelines keeps machine learning code cleaner, easier to maintain, easier to move to produc...
The Causal Impact model lets you examine ecommerce and marketing time series data to understand w...
Learn how to use Python to scrape and parse an XML sitemap, crawl and scrape a site, connect the ...
Learn how to add days and subtract days from dates in Pandas using the Python timedelta function ...
Google Analytics demographics and interests data are a useful way to quickly understand the custo...
Learn how to find striking distance keywords in Google Search Console API data with Python and im...
Lead scoring is a commonly used CRM technique in most B2B e-commerce sites. Here's how the variou...
By assigning or removing tags to subscribers using the Mailchimp marketing API you can create pow...
Learn how to use EcommerceTools to create monthly Google Search Console API reports that let you ...
Learn how to use Decision Trees to engineer or derive new features from your existing data and im...
Learn how to use the Mailchimp API in Python by creating email marketing reports using Pandas and...
The eBay SDK allows developers to search and retrieve eBay listings using a Python API. Here's ho...
Zenpy is an unofficial Zendesk API for Python that allows you to export and update tickets. Here'...
EcommerceTools makes it quick and easy to query the Google Search Console API and display the dat...
The GSpread package makes it quick and easy to read Google Sheets spreadsheets from Google Drive ...
The Lin Rodnitzky Ratio is designed to assess paid search account management quality. Here's how ...
By identifying products that are regularly replenished and contacting customers when they are run...
If you are considering learning data science there are now hundreds of online data science course...
Customer segmentation is the process of grouping customers based on shared characteristics in ord...
Ecommerce purchase intention models predict the probability of each customer making a purchase, s...
Learn how to create a classification model using XGBoost and scikit-learn in Python by classifyin...
Use CatBoost to create an employee churn model that will predict which of your staff is going to ...
Learn how to use create a Python RSS reader using Requests-HTML to read an RSS feed, parse the fe...
Learn how to use EcommerceTools to create automated meta descriptions via deep learning and the B...
Using Python for SEO is really catching on. There are loads of ways you can use Python SEO projec...
Learn how to identify internal and external links through web scraping in Python and help identif...
Marketing Mix Models (MMMs) let you test what marketing results you'll get from changing the amou...
Here's a quick and easy way to scrape Google search engine results into a Pandas dataframe in jus...
The Neural Prophet time series forecasting model was developed by Facebook and is a powerful tool...
Learn how to create a product recommender or product recommendation system in Python using Pandas...
There are dozens of use cases for ecommerce data science, covering everything from segmentation t...
To save time, I created a Python package for generating PDF reports and presentations. Here's how...
Here's how you can use GAPandas to create monthly analytics reports on marketing and ecommerce da...
EcommerceTools makes it quick and easy to segment your customers using a range of powerful techni...
The EcommerceTools package lets you check SERPs, examine robots.txt files, analyse Core Web Vital...
Learn how to use the Isolation Forest or iForest algorithm in sklearn for automated outlier detec...
K means clustering is the most widely used machine learning algorithm and is well-suited to custo...
Creating a value-based segmentation using RFM and ABC is a great way to tell the good customers f...
Customer cohort analysis examines differences between customers over time and is a powerful tool ...
Machine translation systems, such as Google Translate, make it quick and easy to bulk translate p...
Discover how to identify the causes of customer churn using Cox's Proportional Hazards model, so ...
Learn how to detect near duplicate content using the Longest Matching Subsequence (LMS) technique...
Learn how to use the Anomaly Detection Toolkit (ADTK) to identify anomalies in ecommerce data ext...
Learn how to keep tabs on your competitors' pricing by building an ecommerce price scraper that u...
Learn how to create a non-contractual churn model to let you predict churn and identify which cus...
Make your ecommerce customer service team more efficient by classifying their support emails auto...
Calculating Customer Lifetime Value is hard to do right. Learn how to calculate CLV using the BG/...
Learn how to use Transformer models to automatically generate summaries from ecommerce product de...
Use quantile-based discretization and K-means clustering to calculate RFM scores to your customer...
Learn how to use Extractive Question Answering or EQA models to assess the quality of your ecomme...
Learn how to shape your product, content, and pricing strategy by analysing product consumption a...
Although Spintax was mainly used for the production of low quality articles, and emails from Nige...
Learn how to use ensemble models that utilise bagging, boosting, and stacking to generate better ...
Learn to scrape more efficiently by extracting Schema.org metadata in JSON-LD, Microdata, and Ope...
Google’s People Also Ask or PAA boxes are increasingly common for popular search terms and are wo...
Learn to scrape Google search results using Python and save loads of time and collect data that a...
Time series decomposition lets you separate the trend and seasonality in your data so you can see...
Learn how to use Python to connect your Google Search Console API data to your Google Analytics R...
Learn how to use Python to identify the most popular SEO keywords linked to your search term by s...
Spelling and grammar issues on product detail pages can make your site look unprofessional. Here’...
Learn how to engineer customer purchase latency features based on the time between each customer'...
Learn how to create targeted B2B company datasets for free using Python, Pandas, and Companies Ho...
Want to analyse the data science and data engineering job market? Here's a quick guide to buildin...
Product matching algorithms find identical products on ecommerce sites so users can compare produ...
Learn how to use NLP techniques to create a Multinomial Naive Bayes sklearn product classificatio...
B2B ecommerce retailers spend large amounts on acquiring the addresses of potential customers to ...
Learn how to use Python to count the number of indexed pages a website has to help you monitor it...
The safety stock calculation and reorder point calculation can greatly reduce the likelihood of c...
Understand the most important metrics for operations managers and learn how to calculate them in ...
Learn how to calculate marketing metrics such as CPM, CPC, conversion rate, ROMI, ROI, ROAS, CPO,...
Customer experience metrics and customer satisfaction metrics drive customer retention, so it's v...
Category management metrics can let you understand product sales and be more strategic in your pr...
The Google Knowledge Graph powers the Knowledge Panels and infobox elements of Google’s search re...
Catalogues may be living on borrowed time, but catalogue marketing data science techniques have b...
Use the Kneedle algorithm to detect the knee or elbow point when k means clustering so you define...
Extruct allows you to reveal a site's Schema.org metadata implementation, so you can build a more...
If you're downloading large zipped datasets via automated Python scripts, you may need to unzip o...
PHP serialized arrays and objects are common in ecommerce database schemas. This is how you unser...
PyGAMP allows you to insert data into Google Analytics using the Measurement Protocol API in Pyth...
Learn how to use web scraping technologies, including urllib and Beautiful Soup, to scrape a webs...
The robots.txt file includes potential useful information for crawlers and spiders, and is easy t...
Learn how to apply web scraping tools to scrape a site's content and parse the page titles and me...
404 errors and 301 redirect chains can be damaging to the performance of a website and impact the...
Learn how to use the TinyPNG API in Python to bulk resize and compress images to improve site per...
Learn how to apply tokenization, stopword removal, Porter stemming, and re-joining to preprocess ...
XML sitemaps are a great way to gain insight on your competitors’ websites and identify pages to ...
When analysing web data, it’s common to need to parse URLs and extract the domain, directories, q...
Learn how to use Python to identify keyword cannibalisation which occurs when multiple pages comp...
The Python urllib package allows you to download files from remote servers to use in your project...
Can you tell when someone is taking the piss, when they haven't used a winking smiley? In this pr...
Learn the Natural Language Processing techniques you need to use to identify fake news from real ...
Learn how to calculate the Economic Order Quantity or EOQ for a product to minimise holding costs...
Requests-HTML wraps up the best bits from Requests and Beautiful Soup packages to create a web sc...
Core Web Vitals are performance metrics that measure the quality of the user experience and are n...
Learn how to use PandaSQL and query the data in your Pandas dataframes using SQL queries instead ...
Learn how you can use Python to identify how many non-ranking pages your site has and check wheth...
By accessing Google Search Console API data using Python you'll have access to whatever data you ...
Search intent classification aims to categorise search queries by user intent. But how do you do ...
The Screaming Frog SEO Spider is widely used in digital marketing and ecommerce and has a powerfu...
It’s really easy to send Slack messages using Python. In this project, we’ll create a really basi...
Learn how to use GeoPy, Nominatim, and Folium to geocode and plot Pizza Express branches in the v...
Pandas is a powerful tool for marketers, especially those involved in paid search advertising. He...
Beautiful Soup is one of the most powerful libraries for performing web scraping in Python. Here'...
Despite the growing demand, many people still don’t understand the difference between a data scie...
Learn how to use the Don’t Repeat Yourself and Do One Thing techniques to help you create Python ...
Want to dumb-down your plots and charts for your target audience? CuteCharts allows you to create...
Funnels are one of the most useful and intuitive data visualisations used in ecommerce and market...
Learn how and why following Python style guidelines can make your code easier to understand, revi...
The SQLite relational database management system is fast, lightweight, and easy to use. Here's ho...
Python operators are one of the most important components of the language to grasp. Here’s a basi...
Lists are one of the most widely used data storage objects or data types within Python and are us...
Learn how to use Git for your data science projects so you can keep your code backed-up and share...
Using docstrings in Python makes it easier to see what functions do, what arguments they accept, ...
The Pandas value_counts() function is great for calculating the number of occurrences of a value ...
Querying MySQL and other databases using Pandas in Jupyter notebooks will change the way you work...
Python makes it very straightforward to open, read, and write data to files. Here's a quick guide...
If you're learning data science, there are four Python data science libraries you absolutely need...
Word clouds, tag clouds, or wordles are an intuitive way to present text data to non-technical pe...
Understanding the statistical distribution of data is a crucial step in machine learning. Here’s ...
The Venn diagram is one of the most intuitive data visualisations for showing the overlap between...
Line charts or line plots are among the most commonly used graphs in data science. Here’s how you...
Learn how to create barplots or bar charts for comparing and visualising categorical data in Pyth...
Machine learning models make predictions from correlations between features and the target, so fi...
There’s more to visualising categorical data than bar charts. Here’s a selection of the other cha...
The NVIDIA Data Science Stack is the quickest way to setup the drivers and packages needed for GP...
Nativefier makes it easy to create Ubuntu desktop applications from websites using Electron. Here...
Here's how you can create a Gnome desktop entry shortcut launcher icon to start up Docker and ope...
Datasets for the product matching models required to verify price comparisons are hard to find. H...
Building your own data science workstation or deep learning workstation isn’t that difficult and ...
Heatmaps make visualising temporal data much easier. Here’s how you can create custom web analyti...
Learn how to assign simple labels to your RFM data and visualise them using treemaps to help make...
Scatterplots are a great way to visualise the distribution of data and the relationship between t...
Pandas histograms are one of the best ways to visualise the statistical distributions of data dur...
The Seaborn boxplot, or box-and-whisker diagram, is a great way to visualise the statistical dist...
SMOTE, the Synthetic Minority Oversampling Technique, is one of the best ways to handle imbalance...
Matt Clarke explains how you can use Recursive Feature Elimination with Cross Validation or RFECV...
Model selection and hyperparameter tuning can greatly improve model performance. Learn how to use...
Learn how to use Category Encoders to transform and convert categorical variables to numeric data...
Learn a range of useful techniques to select, filter, and subset data stored in Pandas dataframes...
Machine learning or ML models can take days to train. Pickle save and Pickle load allows you to s...
The Pandas resample function lets you group time series data by day, week, month, or year so it c...
Learn how to use Python and Pandas to reformat dates and datetimes so you can display them in you...
Learn how to import data into Pandas from a wide range of different data sources, from CSV and Ex...
Learn how to group and aggregate transactional data using Pandas to create new datasets allowing ...
Creating accurate ecommerce time series forecasts using models such as ARIMA can be tricky. The P...
Learn how to improve outbound sales using a machine learning response model that maximises your s...
Want to get started with sklearn linear regression? Learn to use Python, Pandas, and scikit-learn...
Google Trends data is now being used in a range of models. Here’s how you can access the data usi...
Learn how to use image hashing or image fingerprinting to find visually similar images or duplica...
The ABC XYZ inventory classification model is built on top of ABC inventory analysis and helps yo...
Learn how to use Google Secret Manager to create secure environmental variables to hold your sens...
Text annotation techniques like sequence labeling are vital in NLP, but are tedious, time-consum...
Google Data Studio doesn’t include native support for Python, but you can still import data from ...
Learn how to import data into the Google BigQuery serverless data warehouse platform using Python...
Learn some simple techniques you can apply using Pandas and Numpy to create dummy, synthetic, or ...
Learn how to create image datasets for machine learning image classification models using Python ...
Learn how to create an ABC inventory classification model in Python so your procurement manager t...
MySQL databases are usually configured to only allow secure connections via SSH. Here’s how to cr...
To automate Google Analytics API reports for Google Data Studio you’ll need to know how to calcul...
Data binning or bucketing is a very useful technique for both preprocessing and understanding or ...
Doccano is a text annotation platform for NLP that makes it much quicker and easier to label and ...
Here’s a selection of some of the most useful datasets I’ve found for building machine learning m...
The Beta-Geometric Negative Binomial Distribution or BG/NBD model lets you predict which customer...
Learn how to use web scraping and NLP to shape your ecommerce strategy by identifying what influe...
Learn how to create a powerful and extensible business intelligence (BI) platform for your ecomme...
Apache Druid is a real-time high performance analytics data store for big data that makes running...
Learn how to create a Docker container for your MySQL or MariaDB database server so you can extra...
Category Encoders make it much easier to encode categorical variables during the machine learning...
Learn how to create an Apache Airflow data pipeline and see why it is one of the most widely used...
Learn how to use Pandas to create a dynamic ecommerce trading calendar of special trading events,...
The Dell Precision 7750 mobile workstation is aimed at data scientists who want a laptop for GPU-...
Learn why ecommerce retailers and marketplaces are creating Product Attribute Extraction (PAE) mo...
Next-Product-To-Buy or NPTB models can predict not only what a customer will buy, but also when t...
Machine learning (ML) is a branch of artificial intelligence (AI) and allows models to make predi...
Unlike response or propensity models, uplift models let you identify customers who will only buy ...
Learning to Rank or LTR models improve the performance of on-site search results on ecommerce web...
Learn how to use the Pandas melt function to reshape wide format data so you can use it in your m...
Learn how to use the mlxtend Apriori algorithm to run a Market Basket Analysis on Google Analytic...
Learn how to use Natural Language Understanding models (NLU) via PyTorch and Hugging Face Transfo...
Learning to use Docker for data science projects will make configuring, deploying, and sharing mo...
Every scikit-learn model has hyper-parameters you can tune to obtain improvements. Here’s how to ...
Setting up TensorFlow, Keras, CUDA, and CuDNN can be a painful experience on Ubuntu 20.04. Here i...
Here's how you can use Python, Selenium, and Extruct to create a headless web browser and scrape ...
Learn how to automate the collection of website technology data from your competitors using Built...
Facial recognition is now very effective and has become part of everyday life. Here's how to use ...
Learn how to use Deezer's TensorFlow powered Spleeter model to separate music into vocals and acc...
Pandas lets you create dataframes from almost any type of data, including lists, dictionaries, tu...
Learn how to use item-based and user-based collaborative filtering to create a powerful recommend...
Learn how to classify images using Keras and TensorFlow by building the 'Hotdog, Not Hotdog' Conv...
Learn how to use a recurrent neural network and the Long Short-Term Memory model to analyse senti...
Learn how to use GAPandas to query the Google Analytics API and view, analyse, and visualise your...
Do your XGBoost machine learning models take an age to run? You could make them several times fas...
To learn data science techniques you’ll need the right kind of datasets. Thankfully, many are eas...
Regular expressions, or regexes, are widely used in data science for matching specific patterns i...
Learn how to use the mean encoding technique to generate powerful new features from your data to ...
The confusion matrix can tell you more about your model than the accuracy score. We build a model...
Cleverly filling in the gaps when numeric data is missing from your dataset can often boost the p...
In time series datasets dates often hold the key to improving performance, but they need to be tr...
Learn how to create a Python virtual environment for your Jupyter notebook using venv and virtual...
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