Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: ManyToMany Model Solution 02
In this video, we will cover ManyToMany model solution 02. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Optional Estimation: MLE
In this video, we will cover MLE.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Optional Estimation: Logistic Regression
In this video, we will cover logistic regression.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Optional Estimation: DNN
In this video, we will understand DNN.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Object Detection: HOG Features
In this video, we will cover HOG features. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Multiple Random Variables: Multivariate Gaussian
In this video, we will cover multivariate Gaussian.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Image Processing: Edge Detection
In this video, we will cover edge detection. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in CNNs: Example Setup
In this video, we will cover example setup. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Yolo: Yolo Algorithm
In this video, we will cover Yolo algorithm. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: Attention Model Optional
In this video, we will cover attention model optional. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section,...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - TensorFlow: TensorFlow Text Classification Example using RNN
In this video, we will cover TensorFlow text classification example using RNN. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Sentiment Classification using RNN: Vectorizer
In this video, we will cover Vectorizer. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will cover...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Vector Derivatives
In this video, we will cover vector derivatives. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Rank
In this video, we will cover Rank. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Positive Semi Definite Matrix
In this video, we will cover a positive semi definite matrix. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Orthonormal Basis
In this video, we will cover Orthonormal Basis. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Coordinates Versus Dimensions
In this video, we will cover coordinates versus dimensions. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Classification Prediction Probabilities Exercise Solution
In this video, we will cover classification prediction probabilities exercise solution. This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and...
Curated Video
Selenium WebDriver with Java - Basics to Advanced and Frameworks - What are Java Collections?
This video explains Java Collections. This clip is from the chapter "Core Java Tutorial - Part 3 - Collections Application Programming Interface (API)" of the series "Selenium WebDriver with Java - Basics to Advanced and Frameworks".This...
Curated Video
Reflection and Translation of a Triangle
This video shows the process for solving the problem presented in IGCSE A June 2018 paper 1HR Q3, which involves performing two basic transformations of a triangle: reflection and translation. Students will learn how to reflect a point...
Curated Video
Proving Collinearity of Points Using Vector Methods
This video shows the process for solving the problem presented in IGCSE A June 2018 paper 2HR Q23, which involves vector theory. We will use vector methods to find the position vectors of the points and show that they are linearly...
TMW Media
Momentum And Impulse: Momentum
What is the equation for momentum? Why is this equation useful? Momentum And Impulse, Part 1
Curated Video
Evaluate visual representations of data that models real-world phenomena or processes : Advanced Features and Limitations
From the section: NLP Visualization and Model Experimentation. Visualize text data and view data embeddings. View and track hyperparameter tuning and display training configurations to run reproducible experiments. Here, let’s...
Math Fortress
Calculus III: The Dot Product (Level 1 of 12)
This video goes over the dot product also known as the scalar product. This video covers the geometric interpretation of the dot product by going over 5 distinct cases where the angle between the vectors varies.