Locally Deployed Small Language Model TinyLlama
Jude Michael Teves
Locally Deployed Small Language Model TinyLlama
0:20
Transfer Learning Coding
Jude Michael Teves
Transfer Learning Coding
10:49
Convolutional Neural Networks Coding
Jude Michael Teves
Convolutional Neural Networks Coding
8:50
Model Interpretability - Model-Agnostic Methods Coding
Jude Michael Teves
Model Interpretability - Model-Agnostic Methods Coding
10:16
Model Interpretability - Interpretable Models Coding
Jude Michael Teves
Model Interpretability - Interpretable Models Coding
5:20
Model Interpretability - Model-Agnostic Methods
Jude Michael Teves
Model Interpretability - Model-Agnostic Methods
6:30
Model Interpretability - Interpretable Models
Jude Michael Teves
Model Interpretability - Interpretable Models
2:30
Model Interpretability - Introduction
Jude Michael Teves
Model Interpretability - Introduction
3:53
Big Data Introduction
Jude Michael Teves
Big Data Introduction
22:10
Big Data Analytics - OLTP vs OLAP, Star vs Snowflake Schemas, and Analytics Deployment
Jude Michael Teves
Big Data Analytics - OLTP vs OLAP, Star vs Snowflake Schemas, and Analytics Deployment
16:33
Recommender Systems pt8 - Collaborative Filtering Coding
Jude Michael Teves
Recommender Systems pt8 - Collaborative Filtering Coding
14:08
Recommender Systems pt7 - Latent Factor Models Collaborative Filtering
Jude Michael Teves
Recommender Systems pt7 - Latent Factor Models Collaborative Filtering
10:45
Recommender Systems pt6 - User and Item Based Collaborative Filtering
Jude Michael Teves
Recommender Systems pt6 - User and Item Based Collaborative Filtering
9:00
Recommender Systems pt4 - Similarity Metrics
Jude Michael Teves
Recommender Systems pt4 - Similarity Metrics
6:39
Recommender Systems pt5 - Similarity Metrics Coding
Jude Michael Teves
Recommender Systems pt5 - Similarity Metrics Coding
3:49
Recommender Systems pt3 - Content based Filtering Coding
Jude Michael Teves
Recommender Systems pt3 - Content based Filtering Coding
13:09
Recommender Systems pt2 - Content based Filtering
Jude Michael Teves
Recommender Systems pt2 - Content based Filtering
8:21
Recommender Systems pt1 - Overview
Jude Michael Teves
Recommender Systems pt1 - Overview
16:07
Association Rule Learning pt2 - Coding
Jude Michael Teves
Association Rule Learning pt2 - Coding
8:08
Association Rule Learning pt1 - Foundations
Jude Michael Teves
Association Rule Learning pt1 - Foundations
15:03
Decision Tree pt2 - Impurity
Jude Michael Teves
Decision Tree pt2 - Impurity
21:26
Decision Tree pt1 - Foundations
Jude Michael Teves
Decision Tree pt1 - Foundations
11:28
Naive Bayes pt2 - Distributions
Jude Michael Teves
Naive Bayes pt2 - Distributions
8:10
Naive Bayes pt1 - Foundations
Jude Michael Teves
Naive Bayes pt1 - Foundations
14:03
Practical ML pt6.5 - More ML Tips
Jude Michael Teves
Practical ML pt6.5 - More ML Tips
3:24
Low-cost portable PC setup #raspberrypi #computer
Jude Michael Teves
Low-cost portable PC setup #raspberrypi #computer
0:15
Programming and Robotics Workshop - Teaching Python, electronics, and Raspberry Pi.
Jude Michael Teves
Programming and Robotics Workshop - Teaching Python, electronics, and Raspberry Pi.
0:13
Preprocessing - Regular Expressions
Jude Michael Teves
Preprocessing - Regular Expressions
15:25
Preprocessing - Handling Text Inconsistencies
Jude Michael Teves
Preprocessing - Handling Text Inconsistencies
10:11
ASEAN Data Science Explorers 2023 Enablement Session
Jude Michael Teves
ASEAN Data Science Explorers 2023 Enablement Session
1:34:49
Data Collection - Selenium: Scraping Dynamic Webpages
Jude Michael Teves
Data Collection - Selenium: Scraping Dynamic Webpages
9:54
Data Collection - Web Scraping
Jude Michael Teves
Data Collection - Web Scraping
12:45
Data Mining - Overview
Jude Michael Teves
Data Mining - Overview
14:38
Neural Network pt5 - Code
Jude Michael Teves
Neural Network pt5 - Code
16:47
Neural Network pt4 - Architectures
Jude Michael Teves
Neural Network pt4 - Architectures
6:46
Neural Network pt3 - Activation Functions
Jude Michael Teves
Neural Network pt3 - Activation Functions
8:53
Neural Network pt2 - Forward and Backpropagation
Jude Michael Teves
Neural Network pt2 - Forward and Backpropagation
9:16
Neural Network pt1 - Foundations
Jude Michael Teves
Neural Network pt1 - Foundations
9:54
K-means pt4 - Interpreting the results
Jude Michael Teves
K-means pt4 - Interpreting the results
2:54
K-means pt3 - Choosing the number of centroids and Coding
Jude Michael Teves
K-means pt3 - Choosing the number of centroids and Coding
10:54
K-means pt2 - Visualizing K-means
Jude Michael Teves
K-means pt2 - Visualizing K-means
10:01
K-means pt1 - Foundations
Jude Michael Teves
K-means pt1 - Foundations
3:53
Practical ML pt6 - ML Tips
Jude Michael Teves
Practical ML pt6 - ML Tips
4:50
Practical ML pt7 - Code
Jude Michael Teves
Practical ML pt7 - Code
2:32
Practical ML pt5 - Bias-Variance Analysis
Jude Michael Teves
Practical ML pt5 - Bias-Variance Analysis
10:36
Practical ML pt4 - Model Evaluation
Jude Michael Teves
Practical ML pt4 - Model Evaluation
11:13
Practical ML pt3 - ML Pipeline
Jude Michael Teves
Practical ML pt3 - ML Pipeline
6:37
Practical ML pt2 - Feature Engineering
Jude Michael Teves
Practical ML pt2 - Feature Engineering
6:10
Practical ML pt1 - Exploratory Data Analysis
Jude Michael Teves
Practical ML pt1 - Exploratory Data Analysis
5:10
ML Linear and Logistic Regression Code
Jude Michael Teves
ML Linear and Logistic Regression Code
6:57
ML Logistic Regression pt1 - Intuition
Jude Michael Teves
ML Logistic Regression pt1 - Intuition
6:25
ML Linear Regression pt8 - Inference
Jude Michael Teves
ML Linear Regression pt8 - Inference
1:33
ML Linear Regression pt7 - Gradient Descent Types
Jude Michael Teves
ML Linear Regression pt7 - Gradient Descent Types
3:35
ML Linear Regression pt6 - Gradient Descent for Linear Regression
Jude Michael Teves
ML Linear Regression pt6 - Gradient Descent for Linear Regression
5:03
ML Linear Regression pt5 - Gradient Descent Manual Computation
Jude Michael Teves
ML Linear Regression pt5 - Gradient Descent Manual Computation
19:53
ML Linear Regression pt4 - Gradient Descent Algorithm
Jude Michael Teves
ML Linear Regression pt4 - Gradient Descent Algorithm
2:00
ML Linear Regression pt3 - Ordinary Least Squares
Jude Michael Teves
ML Linear Regression pt3 - Ordinary Least Squares
2:54
ML Linear Regression pt2 - Optimization using Calculus
Jude Michael Teves
ML Linear Regression pt2 - Optimization using Calculus
4:18
ML Linear Regression pt1 - Intuition
Jude Michael Teves
ML Linear Regression pt1 - Intuition
13:19
ML K-Nearest Neighbors (KNN) pt4 - Coding
Jude Michael Teves
ML K-Nearest Neighbors (KNN) pt4 - Coding
6:05
ML K-Nearest Neighbors (KNN) pt3 - Choosing k
Jude Michael Teves
ML K-Nearest Neighbors (KNN) pt3 - Choosing k
6:52
ML K-Nearest Neighbors (KNN) pt1 - Foundations
Jude Michael Teves
ML K-Nearest Neighbors (KNN) pt1 - Foundations
13:57
ML K-Nearest Neighbors (KNN) pt2 - Distance measurement and Curse of dimensionality
Jude Michael Teves
ML K-Nearest Neighbors (KNN) pt2 - Distance measurement and Curse of dimensionality
5:39
Python Basic Preprocessing Tutorial
Jude Michael Teves
Python Basic Preprocessing Tutorial
16:49
Python Pandas Tutorial
Jude Michael Teves
Python Pandas Tutorial
15:53
Python Matplotlib Tutorial
Jude Michael Teves
Python Matplotlib Tutorial
5:03
Python Numpy Tutorial
Jude Michael Teves
Python Numpy Tutorial
9:45
Facial Recognition with Audio Generator Circuit
Jude Michael Teves
Facial Recognition with Audio Generator Circuit
0:06
How Machines Understand Human Language
Jude Michael Teves
How Machines Understand Human Language
1:07:06
Python and Machine Learning for Beginners
Jude Michael Teves
Python and Machine Learning for Beginners
1:15:59
ai generated music
Jude Michael Teves
ai generated music
0:26
Facial Recognition and Thermal Identification
Jude Michael Teves
Facial Recognition and Thermal Identification
0:16