Machine Learning Guide

MLG 024 Tech Stack

MLG 023 Deep NLP 2

This podcast episode explores different aspects of recurrent neural networks (RNNs) and their applications in natural language processing (NLP) tasks, stock market predictions, and time series analysis. The host discusses the types of neural networks, including RNNs, and introduces solutions to the vanishing and explod...

MLG 022 Deep NLP 1

This podcast episode explores the impact of deep learning, particularly recurrent neural networks (RNNs), on natural language processing (NLP). It discusses the concepts of feature engineering and feature learning in deep learning, as well as the distinction between sequence and non-sequence models in NLP. The episode ...

MLG 020 Natural Language Processing 3

This podcast episode explores the various tools and techniques used in shallow natural language processing (NLP) algorithms. The episode discusses high-level goals such as text classification, sentiment analysis, search engines, and question answering, and the tools used to achieve them, including part of speech taggin...

MLG 019 Natural Language Processing 2

This podcast episode explores the key concepts and algorithms in natural language processing (NLP). It introduces classical NLP algorithms, including shallow learning and deep learning approaches, highlighting the importance of understanding shallow algorithms despite the prevalence of deep learning. The episode covers...

MLG 018 Natural Language Processing 1

This podcast episode explores the concept of specialization in machine learning, focusing on Natural Language Processing (NLP) as a specific field within machine learning. NLP is described as a unique subfield with its own set of algorithms and techniques that deal with text, syntax, and semantics. The episode highligh...

MLG 017 Checkpoint

MLG 016 Consciousness

MLG 015 Performance

This podcast episode explores the concept of performance evaluation in machine learning and highlights the importance of choosing the right metrics and techniques to enhance the performance of machine learning models. It covers topics such as error functions, performance metrics, precision and recall, the confusion mat...

MLG 014 Shallow Algos 3

This podcast episode explores the concept of anomaly detection and the use of the bell curve in statistics. Anomaly detection systems are used to identify unusual events or outliers in various fields, such as fraud detection and server monitoring. The bell curve, also known as the Gaussian distribution or normal distri...

MLG 013 Shallow Algos 2

This podcast episode explores various shallow learning algorithms, including decision trees, support vector machines (SVMs), and naive Bayes. It emphasizes the importance of selecting the most appropriate algorithm for a given task by considering factors such as the specific task, type of data, and available resources....

MLG 012 Shallow Algos 1

This podcast episode explores the importance of shallow learning algorithms as foundational knowledge for machine learning engineers. It highlights the limitations of deep learning and the benefits of using shallow learning algorithms for specific problem types. The episode provides an overview of commonly used shallow...

MLG 010 Languages & Frameworks

This Machine Learning Guide podcast episode (Episode 10) focuses on comparing programming languages and frameworks for machine learning. The host discusses various options, including C/C++, R, MATLAB/Octave, Julia, Java/Scala, and Python, evaluating their strengths and weaknesses for different machine learning tasks (...

MLG 009 Deep Learning

This podcast episode delves into the world of deep learning and neural networks, highlighting their significance in the field of artificial intelligence. It explores the hierarchical structure of machine learning, with deep learning as a subset of supervised learning. The episode discusses the unique characteristics of...

MLG 008 Math

MLG 007 Logistic Regression

This podcast episode introduces logistic regression, a classification algorithm that uses a linear regression algorithm to predict the probability of an input belonging to a particular class. It explains the concepts of logits, argmax, sigmoid function, error function, gradient descent, and composability in machine lea...

MLG 006 Certificates & Degrees

MLG 005 Linear Regression

This podcast episode introduces linear regression as a fundamental machine learning algorithm and discusses its hierarchical nature within supervised learning. It explains the concept of the hypothesis function in linear regression and its role in making predictions. The episode also covers the cost function and the us...

MLG 004 Algorithms - Intuition

This podcast episode explores the fundamentals of machine learning, including the three-step process of infer or predict, error or loss, and train or learn. It provides examples of how these steps operate in the contexts of playing chess and predicting house prices. The episode also introduces concepts such as algorith...

MLG 003 Inspiration