Tag: data science
Total: 58 Posts
Posts of Tag: data science
  1. K-Means Clustering with the Elbow method

    .lazyload-placeholder { display: none; } K-means clustering is an unsupervised learning algorithm that groups data based on each point euclidean distance to a central point called centroid. The centroids are de...Learn More
    PythonAlgorithmMachine Learningscikit-learndata science
  2. How to Fill NaNs in a Pandas DataFrame

    .lazyload-placeholder { display: none; } Missing values are common and occur either due to human error, instrument error, processing from another team, or otherwise just a lack of data for a certain observation...Learn More
    Pythondata sciencepandasnumpy
  3. Split Train, Test and Validation Sets with Tensorflow Datasets - tfds

    Introduction Tensorflow Datasets, also known as tfds is is a library that serves as a wrapper to a wide selection of datasets, with proprietary functions to load, split and prepare datasets for Machine and Deep...Learn More
    PythonMachine LearningDeep LearningValidationdata sciencetensorflow
  4. Keras Callbacks: Save and Visualize Prediction on Each Training Epoch

    Introduction Keras is a high-level API, typically used with the Tensorflow library, and has lowered the barrier to entry for many and democratized the creation of Deep Learning models and systems. When just sta...Learn More
    PythonMachine Learningdata scienceartificial intelligencekerastensorflow
  5. Feature Scaling Data with Scikit-Learn for Machine Learning in Python

    Introduction Preprocessing data is an often overlooked key step in Machine Learning. In fact - it's as important as the shiny model you want to fit with it. Garbage in - garbage out. You can have the best mod...Learn More
    PythonMachine Learningdata science
  6. Hands-On House Price Prediction - Deep Learning in Python with Keras

    In this short series of guides, we'll be taking a look at a hands-on house price prediction. We'll be using Keras, the deep learning API built on top of TensorFlow to train a neural network to predict the price...Learn More
    PythonMachine Learningdata scienceartificial intelligencekerastensorflow
  7. Scikit-Learn's train_test_split() - Training, Testing and Validation Sets

    Introduction Scikit-Learn is one of the most widely-used Machine Learning library in Python. It's optimized and efficient - and its high-level API is simple and easy to use. Scikit-Learn has a plethora of conve...Learn More
    PythonMachine LearningValidationscikit-learndata scienceartificial intelligencetesting
  8. Searching and Replacing Words in Python with FlashText

    Introduction In this tutorial, we'll explain how to replace words in text sequences, with Python using the FlashText module, which provides one of the most efficient ways of replacing a large set of words in a ...Learn More
    Pythondata science
  9. Calculating Spearman's Rank Correlation Coefficient in Python with Pandas

    Introduction This guide is an introduction to Spearman's rank correlation coefficient, its mathematical calculation, and its computation via Python's pandas library. We'll construct various examples to gain a b...Learn More
    Pythondata sciencedata visualizationpandasmathsnumpyseaborn
  10. Guide to Multidimensional Scaling in Python with Scikit-Learn

    Introduction In this guide, we'll dive into a dimensionality reduction, data embedding and data visualization technique known as Multidimensional Scaling (MDS). We'll be utilizing Scikit-Learn to perform Mult...Learn More
    PythonMachine Learningscikit-learndata scienceartificial intelligencedata visualization
  11. Self-Organizing Maps: Theory and Implementation in Python with NumPy

    Introduction In this guide, we'll be taking a look at an unsupervised learning model, known as a Self-Organizing Map (SOM), as well as its implementation in Python. We'll be using an RGB Color example to train ...Learn More
    PythonMachine Learningdata scienceartificial intelligencenumpytheory
  12. Random Projection: Theory and Implementation in Python with Scikit-Learn

    Introduction This guide is an in-depth introduction to an unsupervised dimensionality reduction technique called Random Projections. A Random Projection can be used to reduce the complexity and size of data, ma...Learn More
    PythonMachine Learningscikit-learndata scienceartificial intelligencenumpytheory