Mlearning.ai

FEBRUARY 15, 2024

Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. Let’s use those fancy algorithms to make predictions from our data. Here I will try to explain what my thought process was during this project. You can refer part-I and part-II of this article.

Data Science 52

Data Science Categorization Algorithm ML 52

Mlearning.ai

APRIL 17, 2023

A step-by-step error analysis for a classification problem, including data analysis and recommendations When it comes to artificial intelligence interviews, one of the most important questions is, “What are the phases of an AI model’s life cycle?” Besides the size, it is significant to discuss the model metrics.

Machine Learning 52

Machine Learning Categorization Data Analysis Neural Network 52

Pickl AI

FEBRUARY 12, 2024

Communication skills Articulating complex ideas, explaining methodologies, and presenting findings in a clear and concise manner are essential components of Data Science roles. The choice of method depends on the nature of the data and the specific requirements of the analysis. Here is a brief description of the same.

Data Science 52

Data Science Machine Learning Algorithm Explainability 52

Mlearning.ai

FEBRUARY 9, 2023

I find that R markdown is most useful for making reports or documents with your analysis. The most common ways to create a written report with data analysis notebooks are: 1. Python, R, SQL) code analysis in jupyter notebook, using Markdown notation — File —Download as (pdf, html, docx, etc) document 2. R markdown (.rmd)

Neural Network 52

Neural Network Data Analysis Machine Learning Categorization 52

Heartbeat

SEPTEMBER 28, 2023

Hands-on Project Why customer churn matters and how to predict it with machine learning, explained step-by-step Photo by Gabrielle Ribeiro on Unsplash Introduction In today’s competitive business environment, retaining customers is essential to a company’s success. Preprocessing Data preprocessing is a critical step.

Machine Learning 52

Machine Learning Categorization ML Data Scientist 52

Pickl AI

MARCH 18, 2024

Cash Flow Statement Track the movement of cash through a company, categorized into operating, investing, and financing activities. Data Analysis Include charts, graphs, or tables to visually represent trends and insights. Interpretation and Insights Explain the meaning behind the data and visuals.

Data Analysis 52

Data Analysis Explainability Automation Categorization 52

Mlearning.ai

APRIL 17, 2023

Without further ado, let’s dive in to our study… Photograph Via : Steven Yu | Pexels, Pixabay Hello, my previous work Analyzing and Visualizing Earthquake Data Received with USGS API in Python Environment I prepared a new work after 3 weeks. Now, I will be conducting an exploratory data analysis study. value_counts().to_dict()

Data Analysis 52

Data Analysis Categorization Explainability ML 52

Mlearning.ai

JULY 2, 2023

The Art of Forecasting in the Retail Industry Part I : Exploratory Data Analysis & Time Series Analysis In this article, I will conduct exploratory data analysis and time series analysis using a dataset consisting of product sales in different categories from a store in the US between 2015 and 2018.

Categorization 52

Categorization Data Analysis Data Science ML 52

Mlearning.ai

FEBRUARY 2, 2023

These mistakes can be broadly categorized into the following, i) Data issues  — There are many issues related to the data which includes improper preprocessing, failure to address the missing values, class imbalance, and data leakage; and non-availability of data to solve the problem at hand.

Machine Learning 52

Machine Learning ML Categorization Data Analysis 52

Mlearning.ai

FEBRUARY 28, 2023

As a data scientist at Cars4U, I had to come up with a pricing model that can effectively predict the price of used cars and can help the business in devising profitable strategies using differential pricing. In this analysis, I: provided summary statistics and exploratory data analysis of the data. MAPE of 43.55

Python 52

Python Data Analysis Explainability Categorization 52

Towards AI

SEPTEMBER 22, 2023

Hello, Data Enthusiast? We know that data is better understood through visualizations. It doesn’t just help us get insights, Visualizations also make things easy to explain our insights to clients or others. So, We can say that learning to make better visualizations is essential for any data enthusiast!

Categorization 62

Categorization Data Scientist Explainability Python 62

Heartbeat

FEBRUARY 8, 2023

R is frequently used for statistical software development, data analysis, and data visualisation because it can handle large data sets with ease. This programming language offers a variety of methods for model training and evaluation, making it perfect for machine learning projects that need a lot of data processing.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Deep Learning 52

PyImageSearch

FEBRUARY 6, 2023

But we would still apply data augmentation to ensure the model doesn’t overfit and generalize well on the test dataset. Data Analysis When working with data, especially supervised learning, it is often a best practice to check data imbalance. format(initial_loss)) print("initial accuracy: {: 2f}".format(initial_accuracy))

Auto-classification 144

Auto-classification Computer Vision Neural Network Deep Learning 144

Towards AI

NOVEMBER 8, 2023

In this post, I will discuss the common problems with existing solutions, explain why I am no longer a fan of Kaggle, propose a better solution, and outline a personalized prediction approach. Before we can do any further analysis, we need to understand the dataset’s goal, how it was prepared, and why it was designed in a particular way.

Categorization 116

Categorization Explainability Machine Learning Data Analysis 116

Pickl AI

JULY 17, 2023

Therefore, it mainly deals with unlabelled data. The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Acquiring unlabelled data from computer systems is easier than labeled data.

Machine Learning 52

Machine Learning Algorithm Categorization Data Analysis 52

Marktechpost

AUGUST 21, 2023

Excel VBA Script Explainer uses AI to explain Excel VBA code, while the Excel VBA Script Generator creates VBA scripts. The Google Sheets Formula Generator and the Google Apps Script Explainer use artificial intelligence to analyze and clarify scripts. The software is available as a free Chrome extension.

Artificial Intelligence 95

Artificial Intelligence Artificial Intelligence AI AI 95

Viso.ai

APRIL 25, 2024

It’s important to note that the categorization of visual dataset bias can vary between sources. However, it is worth noting that even though this class imbalance has a significant impact, they do not explain every disparity in the performance of machine learning algorithms. Do the data agree with harmful stereotypes?

Computer Vision 52

Computer Vision Categorization Algorithm Explainability 52

Heartbeat

MARCH 8, 2023

Source: Author Introduction Text classification, which involves categorizing text into specified groups based on its content, is an important natural language processing (NLP) task. This article will look at how R can be used to execute text categorization tasks efficiently. You can read more about the R language here.

Machine Learning 52

Machine Learning Algorithm Categorization NLP 52

Flipboard

MARCH 22, 2023

Data Wrangler makes it easy to ingest data and perform data preparation tasks such as exploratory data analysis, feature selection, and feature engineering. Next, we want to look for categorical data in our dataset. Add another step and choose Encode categorical.

IDP 100

IDP Data Scientist Categorization Data Quality 100

Snorkel AI

MAY 12, 2023

Together, these data ops efforts ensure that model development time is efficient, model performance is robust, and teams focus more on innovation and customer experience, which is what matters. The piece that connects the model to the application and the data is the explainability of the model. Bayan Bruss: Thanks Kishore.

Machine Learning 52

Machine Learning Data Scientist ML Data Science 52

Snorkel AI

MAY 12, 2023

Together, these data ops efforts ensure that model development time is efficient, model performance is robust, and teams focus more on innovation and customer experience, which is what matters. The piece that connects the model to the application and the data is the explainability of the model. Bayan Bruss: Thanks Kishore.

Machine Learning 52

Machine Learning Data Scientist ML Data Science 52

Viso.ai

JANUARY 2, 2024

Text Processing with CNNs In text processing, CNNs are remarkably efficient, particularly in tasks like sentiment analysis, topic categorization, and language translation. Unlike traditional text processing methods that rely on linear approaches, CNNs can capture hierarchical patterns in text data.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. Define and explain selection bias? Explain it’s working. Define confounding variables.

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Mlearning.ai

JUNE 2, 2023

You can add styled titles and make your code in a blog format which can explain all the steps along the way with diagrams etc. Task like building a section of a software or a part of another code can be categorized under Modular Task’s. Experimental Work Another Important feature of .ipynb ipynb files are a great choice.

Python 52

Python Neural Network Computer Vision Machine Learning 52

Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling. R’s workflow support enhances productivity and collaboration among data scientists.

Data Science 52

Data Science Data Scientist Data Analysis Machine Learning 52

DataRobot Blog

DECEMBER 20, 2022

In this educated example , the aim is to predict home prices at the property level in the city of Madrid and the training dataset contains 5 different data types (numerical, categorical, text, location, and images) and +90 variables that are related to these 5 different groups: Market performance. Property performance.

Explainability 59

Explainability Automation Machine Learning AI 59

DataRobot Blog

DECEMBER 1, 2022

This explainability of the predictions can help you see how and why the AI came to these predictions. Set up a data pipeline that delivers predictions to HubSpot and automatically initiate offers within the business rules you set. From there, your marketing team can prioritize and target the clients that will receive coupons.

Machine Learning 52

Machine Learning AI AI Automation 52

Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. When necessary, the platform also enables numerous governance and explainability elements.

Machine Learning 82

Machine Learning Data Mining Data Scientist Artificial Intelligence 82

Dlabs.ai

JUNE 11, 2021

And while the Discovery Process won’t reveal a solution, it will help you explain the context of your project to your stakeholders so that they can buy into the big picture. Because research helps you zero in on possible paths forward. You can also use this step to separate the ‘AI work’ from the ‘non-AI work.’

Machine Learning 52

Machine Learning Categorization Data Analysis Artificial Intelligence 52

AWS Machine Learning Blog

JULY 31, 2023

It also enables you to evaluate the models using advanced metrics as if you were a data scientist. We explain the metrics and show techniques to deal with data to obtain better model performance. Quick model is useful when iterating to more quickly understand the impact of data changes to your model accuracy.

Auto-classification 80

Auto-classification Machine Learning ML Auto-complete 80

Pickl AI

MAY 10, 2023

Categorical values in classification requires the application of logistic regression which is one of the best approaches. K-Nearest Neighbours (kNN) In order to calculate the distance between one data point and every other accomplished parameter through using the metrics of distance like Euclidean distance, Manhattan distance and others.

Machine Learning 52

Machine Learning Algorithm Data Mining Natural Language Processing 52

Applied Data Science

JUNE 1, 2021

We dig into a real-world dataset to search for stories worth telling and explain how common practices in data visualisation sometimes fail to convey the right message. There is no statistical analysis without assumption and no data collection without bias. How do we explain this?

Data Science 52

Data Science Explainability Categorization Business Intelligence 52

Pickl AI

NOVEMBER 6, 2023

Communication and Storytelling: Data Visualization is an effective way to communicate complex data and findings to both technical and non-technical audiences. Visual representations make it easier to convey information, present key findings, and tell compelling stories derived from data.

Data Scientist 52

Data Scientist Data Science Data Analysis Python 52

PyImageSearch

JUNE 19, 2023

By the end of the lesson, readers will have a solid grasp of the underlying principles that enable these applications to make suggestions based on data analysis. All you need to master computer vision and deep learning is for someone to explain things to you in simple, intuitive terms. Or requires a degree in computer science?

Neural Network 56

Neural Network Computer Vision Data Mining Algorithm 56

Heartbeat

MARCH 13, 2023

We first get a snapshot of our data by visually inspecting it and also performing minimal Exploratory Data Analysis just to make this article easier to follow through. Here is the link to the page with both training and test datasets. Finally, we will fill null values in the remaining features with medians.

ML 59

ML Machine Learning Deep Learning Data Science 59

Mlearning.ai

FEBRUARY 25, 2023

Several stages of analysis are needed to find insights and make the right decisions related to data, one of which is data visualization. Data visualization is an essential part of the data analysis process, as it helps to make sense of large and complex data sets.

Data Science 52

Data Science Python Categorization Explainability 52

AWS Machine Learning Blog

MARCH 29, 2023

Exploratory data analysis After you import your data, Canvas allows you to explore and analyze it, before building predictive models. You can preview your imported data and visualize the distribution of different features. This information can be used to refine your input data and drive more accurate models.

Machine Learning 76

Machine Learning ML Data Analysis Data Science 76