Hyperconjugation plays a significant role in stabilizing carbocations, where adjacent alkyl groups donate electron density via sigma bonds to the positively charged carbon, spreading the charge and increasing stability.

Explore the complexities and obstacles hindering true multiculturalism, including systemic prejudice and discrimination based on race, gender, ethnicity, and more. This video explains how historical events and social systems perpetuate...

In this lesson, we will dive into the hardcore process of machine learning and the fundamental elements used in machine learning, like datasets, training and testing data, outliers, models, and so on.
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Learn how to make your own cosmetics, such as moisturizers and eye shadows, from scratch using simple chemical principles. This part covers the basics of emulsions, the importance of hygiene, and how different ingredients cater to...

In this video, we will look at the Amazon Lex bot. Here, we will briefly overview its architecture, define the chat experience and the processes involved, and deploy the chatbot.

In this video, you will learn about the probability distribution table.<br<br/>/>

This clip is from the chapter "Basic Probability" of the series "Deep Learning - Crash Course 2023".In this section, we will talk about probability.

In this video, we will understand how to vectorize the story by defining functions, using the data, and developing an index and tokenizer. We will also determine the maximum story length calculated.

In this video, we will learn to work with tasks that have fixed costs associated with them. We will gain insights into managing and tracking expenses not subject to change during the project.
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In this lesson, we will understand the first model of filtering, content-based filtering, and learn its pros and cons.

Here, we will look at data partitioning, represented as a URL.

In this video, you will learn about the evaluation technique and focus on the online evaluation technique in this lecture.

In this lesson, we will look at the first, second, and third generations of recommender systems.

In this video, we will understand the need for recommender systems and the processes and goals involved.

In this video, you will learn about another deep learning filter called neural collaborative filtering that uses latent and item latent vectors.

In this video, we will discuss deep neural network models that are built on the technique of factorization, and interactions between variables and embeddings are taken into account.

In this video, you will learn about the inference mechanisms for generic recommender systems, including individual interests, candidate generation, ranking and filtering, and item similarities.

As we are aware, recommender systems are migrating from machine learning to deep learning, the reason being to capture non-linear and non-trivial relationships.

With modern philosophy somewhat understood, it's time to pivot and see how logic developed during this time period. First, in the early part of this period, Pascal's wager was an important development, which was followed by the Port...

Learn how to order records in SQL using the ORDER BY keyword. The default sorts in ascending order. We will see examples of both ASC and DESC keywords as well.
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This clip is from the chapter "Order Records in SQL" of the...

Learn what SQL is and how it is based on RDBMS. We will discuss the features and Microsoft SQL Server and SQL Server Management Studio.
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This clip is from the chapter "SQL Introduction" of the series "SQL Server Course for...

This video explains how to create the view in which it shows the top three with maximum % allocation.

This video explains the scope and direction of the table calculations.

In this video, we will explore deep learning concepts in recommender systems, migrating from machine learning to deep learning, and capturing non-linear to non-trivial relationships.
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This clip is from the chapter "Deep...

This video helps you with content-based filtering.<br<br/>/>

This clip is from the chapter "Basic of Recommender Systems" of the series "Recommender Systems with Machine Learning".This section focuses on the basics of recommender systems.