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Apurva Reddy
เข้าร่วมเมื่อ 21 เม.ย. 2012
Part 3: GB Classification, GB Regression and GB Ranking
Showcase of classification techniques using Gradient Boosting frameworks like XGBoost, LightGBM, and CatBoost. Explore regression techniques using Gradient Boosting models to predict continuous outcomes. Implement ranking techniques with Gradient Boosting models, ideal for tasks like search engine ranking.
มุมมอง: 4
วีดีโอ
Part 2: Decision Tree Algo
มุมมอง 421 ชั่วโมงที่ผ่านมา
Dive into the Decision Tree algorithm, a fundamental tool in machine learning.
Part1: Gradient Boosting, Random Forest, AdaBoost
มุมมอง 321 ชั่วโมงที่ผ่านมา
Explore the fundamentals of gradient boosting and its applications. Learn about Random Forest, an ensemble learning method for classification and regression tasks. Understand AdaBoost, a boosting algorithm that combines weak classifiers to create a strong classifier.
Dimensionality Reduction for Images and Tabular Data
มุมมอง 321 ชั่วโมงที่ผ่านมา
Includes dimensionality reduction techniques applied on both image and tabular datasets.
Dimensionality Reduction in Databricks
มุมมอง 321 ชั่วโมงที่ผ่านมา
Scalable implementation of dimensionality reduction on Databricks for large datasets.
Dimensionality Reduction
มุมมอง 721 ชั่วโมงที่ผ่านมา
This notebook explores various dimensionality reduction techniques with interactive visualizations.
Audio Extraction and Clustering
มุมมอง 521 ชั่วโมงที่ผ่านมา
This notebook focuses on clustering audio data. It includes steps for audio feature extraction (e.g., MFCCs, spectrograms) and then applying clustering algorithms to group similar audio samples.
Image Clustering
มุมมอง 321 ชั่วโมงที่ผ่านมา
This notebook shows how to cluster images. It covers image preprocessing, feature extraction (possibly using pre-trained neural networks), and applying clustering algorithms to group similar images.
Documents Clustering
มุมมอง 221 ชั่วโมงที่ผ่านมา
This notebook demonstrates the clustering of text documents. It includes steps for text preprocessing, feature extraction (e.g., TF-IDF), and applying clustering algorithms to group similar documents.
Time Series Clustering
มุมมอง 321 ชั่วโมงที่ผ่านมา
This notebook deals with clustering time series data. It covers techniques specific to time series, such as Dynamic Time Warping (DTW) for measuring similarity between temporal sequences.
Anomaly Detection
มุมมอง 921 ชั่วโมงที่ผ่านมา
This notebook focuses on anomaly detection techniques. It includes time series analysis, using methods like Isolation Forest or Elliptic Envelope to identify outliers in the catfish sales dataset.
DBSCAN Clustering using PyCaret:
มุมมอง 921 ชั่วโมงที่ผ่านมา
This notebook uses the PyCaret library to implement DBSCAN (Density-Based Spatial Clustering of Applications with Noise). DBSCAN is particularly good at finding clusters of arbitrary shape and identifying noise points.
Gaussian Mixture Models Clustering
มุมมอง 321 ชั่วโมงที่ผ่านมา
This notebook explores Gaussian Mixture Models (GMM) for clustering. GMMs are probabilistic models that assume data points are generated from a mixture of Gaussian distributions. It covers EM algorithm implementation and model selection.
Hierarchical Clustering
มุมมอง 221 ชั่วโมงที่ผ่านมา
This notebook demonstrates hierarchical clustering, which creates a tree-like structure of clusters. It includes both agglomerative (bottom-up) and divisive (top-down) approaches, along with visualizations like dendrograms.
K-Means Clustering
มุมมอง 121 ชั่วโมงที่ผ่านมา
This notebook implements K-means clustering from scratch. K-means is an unsupervised learning algorithm that groups similar data points into clusters. The implementation includes steps for initializing centroids, assigning points to clusters, and updating centroids iteratively.
Intelligent Cross-Organizational Process Mining: Transforming Data-Driven Collaboration
มุมมอง 1814 วันที่ผ่านมา
Intelligent Cross-Organizational Process Mining: Transforming Data-Driven Collaboration
Autogluon Tabular Predictor - Multimodal
มุมมอง 102 หลายเดือนก่อน
Autogluon Tabular Predictor - Multimodal
Autogluon Tabular Predictor- QuickStart and InDepth
มุมมอง 262 หลายเดือนก่อน
Autogluon Tabular Predictor- QuickStart and InDepth
Solving a Kaggle competition(IEEE Fraud Detection dataset) using Autogluon
มุมมอง 132 หลายเดือนก่อน
Solving a Kaggle competition(IEEE Fraud Detection dataset) using Autogluon
Solving a Kaggle competition(House Price Predictor) using Autogluon
มุมมอง 92 หลายเดือนก่อน
Solving a Kaggle competition(House Price Predictor) using Autogluon
Time Series Forecasting - Univariate with Exogenous Variables using Pycaret.
มุมมอง 402 หลายเดือนก่อน
Time Series Forecasting - Univariate with Exogenous Variables using Pycaret.
Time Series Forecasting - Univariate without Exogenous Variables using Pycaret.
มุมมอง 252 หลายเดือนก่อน
Time Series Forecasting - Univariate without Exogenous Variables using Pycaret.
Tq so much madi kuda same project akka
I have small dout akka pls help me
Meru chasina ppt slides pampistara akka
hey apporva can i get code of this project please on vishalthecloud@gmail.com