Pickl AI

MARCH 26, 2024

Experimentation and cross-validation help determine the dataset’s optimal ‘K’ value. Distance Metrics Distance metrics measure the similarity between data points in a dataset. Implementing the KNN algorithm involves several steps, from preprocessing the data to training the model and making predictions.

K-nearest Neighbors 52

K-nearest Neighbors Machine Learning Machine Learning Algorithm 52

Mlearning.ai

JANUARY 29, 2024

After doing all these cleaning steps data looks something like this: Features after cleaning the dataset Exploratory Data Analysis Through the data analysis we are trying to gain a deeper understanding of the values, identify patterns and trends, and visualize the distribution of the information.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52

Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. Introduction Welcome Back, Let's continue with our Data Science journey to create the Stock Price Prediction web application.

Python 52

Python AWS Exploratory Data Analysis EDA 52

Mlearning.ai

FEBRUARY 15, 2024

Data Science Project — Predictive Modeling on Biological Data Part III — A step-by-step guide on how to design a ML modeling pipeline with scikit-learn Functions. Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. You can refer part-I and part-II of this article.

Data Science 52

Data Science Decision Trees Exploratory Data Analysis Cross Validation 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. It provides C++ as well as Python APIs which makes it very easier to work on.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

DagsHub

APRIL 21, 2024

Scikit-learn Scikit-learn is a machine learning library in Python that is majorly used for data mining and data analysis. It also provides tools for model evaluation , including cross-validation, hyperparameter tuning, and metrics such as accuracy, precision, recall, and F1-score.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

PyImageSearch

JANUARY 23, 2023

Luckily, OpenCV is pip-installable: $ pip install opencv-contrib-python If you need help configuring your development environment for OpenCV, we highly recommend that you read our pip install OpenCV guide — it will have you up and running in a matter of minutes. For better plots, we have used the matplotlib magic function inline ( Line 30 ).

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

The MLOps Blog

DECEMBER 7, 2022

With all of that, the model gets retrained with all the data and stored in the Sagemaker Model Registry. This is a relatively straightforward process that handles training with cross-validation, optimization, and, later on, full dataset training. After that, a chosen model gets deployed and used in the model pipeline.

ML 52

ML ML AWS ETL 52

Heartbeat

MAY 29, 2023

It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model. It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78