Curated Video
Recommender Systems with Machine Learning - Offline Evaluation Techniques
This video talks about offline evaluation techniques of recommender systems. This clip is from the chapter "Basic of Recommender Systems" of the series "Recommender Systems with Machine Learning".This section focuses on the basics of...
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Recommender Systems with Machine Learning - Section Overview
This video provides an overview of the section. This clip is from the chapter "Basic of Recommender Systems" of the series "Recommender Systems with Machine Learning".This section focuses on the basics of recommender systems.
Curated Video
Master SQL for Data Analysis - Union, Intersect, Except
In this video, you will learn more about the UNION, INTERSECT, JOIN, and EXCEPT operators while combining datasets and tables. This clip is from the chapter "SQL - Combining Data from Multiple Tables" of the series "Master SQL for Data...
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Master SQL for Data Analysis - Loading the eCommerce Datasets
In this video, we will look at the different store datasets of eCommerce that we will use in the eCommerce training project. This clip is from the chapter "Getting Started with Level 2" of the series "Master SQL for Data Analysis".This...
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Recommender Systems: An Applied Approach using Deep Learning - Making Recommendations
In this lesson, you will learn to create a recommendation and use a brute-force algorithm to generate the recommendation. This clip is from the chapter "Project Amazon Product Recommendation System" of the series "Recommender Systems: An...
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Recommender Systems: An Applied Approach using Deep Learning - Candidate Tower and Retrieval System
In this video, you will learn how to create a candidate tower and develop a retrieval system. This clip is from the chapter "Project Amazon Product Recommendation System" of the series "Recommender Systems: An Applied Approach Using Deep...
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Recommender Systems: An Applied Approach using Deep Learning - Make Tensors from DataFrame
In this video, we will continue to check our dataset using a single username. We will use a part of the DataFrame to do so. This clip is from the chapter "Project Amazon Product Recommendation System" of the series "Recommender Systems:...
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Recommender Systems: An Applied Approach using Deep Learning - Data Visualization with WordCloud
In this video, you will learn how to load a dataset for the project being developed, using WordCloud, importing WordCloud, STOPWORDS, and ImageColorGenerator. This clip is from the chapter "Project Amazon Product Recommendation System"...
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Recommender Systems: An Applied Approach using Deep Learning - Download Libraries
In this video, you will learn to implement the Amazon recommender system using the TensorFlow recommender based on specific user behavior. You will learn to download and import particular libraries for the project. This clip is from the...
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Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Comparing Different Machine Learning Models
In this video, we will understand how all machine learning interfaces are the same. This clip is from the chapter "Machine Learning Basics" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this...
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Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - All Data Is the Same
In this video, we will understand how all data is the same as all machine learning interfaces are the same. This clip is from the chapter "Machine Learning Basics" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas...
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Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - What Is a Feature Vector?
In this video, you will learn about a feature vector. This clip is from the chapter "Machine Learning Basics" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this section, we will cover machine...
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Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Regression in Code
In this video, we will practice all that we have learnt in the previous video about regression. This clip is from the chapter "Machine Learning Basics" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in...
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Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Pandas Exercise
In this video, we will have a look at the Pandas exercise that needs to be resolved on our own. This clip is from the chapter "Pandas" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this section,...
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Power BI Tips and Tricks (Includes Time-Saving ChatGPT Prompts) - Power BI Multiple Excel Files with Different File Structures and Modification
This lecture expands on the previous video by exploring the challenges of working with multiple Excel files with different file structures and modifications. We will gain insights into managing these issues effectively in Power BI. This...
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Power BI Tips and Tricks (Includes Time-Saving ChatGPT Prompts) - ChatGPT for Power BI Desktop
ChatGPT chatbot technology with Power BI Desktop integration allows users to interact with data and reports through NLP queries. The video provides step-by-step guidance on setting up the integration and use of ChatGPT to enhance...
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Alteryx Advanced - Exercise 4
In this exercise, we will make use of expert modeling to build an XGBoost classification model that predicts airline passenger satisfaction. We will set the correct datatypes, clean missing values, remove weakly associated features, and...
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Alteryx Advanced - Machine Learning Part 5
This video covers best practices for building and deploying ML models in Alteryx, providing examples of how machine learning can be used to solve specific business problems, customer segmentation, fraud detection, and churn prediction....
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Alteryx Advanced - Machine Learning Part 2
In this video, you will learn to use Alteryx Designer to build and train machine learning models, prepare data for machine learning, how to select appropriate algorithms and techniques, and evaluate model performance. This clip is from...
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Alteryx Advanced - Machine Learning Part 1
This video introduces ML and its applications in data analytics, concepts of supervised and unsupervised learning, and how they can be used to build predictive models and provides an overview of the different algorithms and techniques...
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Alteryx Advanced - Gathering Numbers
In this section, we will look at the transform tool set of Alteryx, which summarizes and rearranges data to prepare it for reporting and analysis. You will learn about weighted averages, running totals, count records tool, and the drag...
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Alteryx Advanced - Wild Matches and Grouping
In this video, we will focus on learning about wild matches and grouping. We will begin with understanding errors when working with data and then learn about tools such as the Fuzzy Match tool; you will learn to purge and merge data. You...
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Alteryx Advanced - Tiles and Binning
In this video, you will learn about grouping data, frequency distribution, and batch records based on metric to begin with. We will look at multiple ways of grouping data using the tile tool and the multiple-field binning tool. This clip...
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Alteryx Advanced - Sampling
In this video, you will learn about sampling, a process of generating a subset from an entire population to provide various qualitive or quantitative statistical information by examining a few selected units at random. We will understand...