Solutions to selected Physics Problems

-
Solutions to selected Physics Problems
Muito Bom!!!
Jackson's "Classical Electrodynamics"
Garrod's "Statistical Mechanics and Thermodynamics"
Hand & Finch's "Classical Mechanics"
Shankar's "Introduction to Quantum Mechanics"
Mathews & Walker's "Methods of Mathematical Physics"

Solutions to selected Physics Problems: "Tanya's Physics Solution page"

Comentários

Postar um comentário

Postagens mais visitadas deste blog

𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐧𝐝𝐨 𝐞𝐦 𝐣𝐨𝐮𝐫𝐧𝐚𝐥𝐬 𝐝𝐞 𝐚𝐥𝐭𝐨 𝐢𝐦𝐩𝐚𝐜𝐭𝐨

-
  𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐧𝐝𝐨 𝐞𝐦 𝐣𝐨𝐮𝐫𝐧𝐚𝐥𝐬 𝐝𝐞 𝐚𝐥𝐭𝐨 𝐢𝐦𝐩𝐚𝐜𝐭𝐨 Prof. João Cláudio Nunes Carvalho A redação de um artigo científico envolve alguma dose de criatividade e inspiração, mas principalmente técnica e conhecimento da lógica de organização do texto. Uma boa introdução de um artigo em gestão e negócios, por exemplo, segue uma estrutura muito parecida na maioria dos journals: ◽ O 𝐩𝐫𝐢𝐦𝐞𝐢𝐫𝐨 parágrafo demonstra o que já se sabe sobre o tema, sem enrolações. O que os estudos dos últimos dois ou três anos estão dizendo sobre o tema? Se você citar estudos de 10, 15 ou 20 anos neste parágrafo, provavelmente seu artigo será rejeitado. ◽ O 𝐬𝐞𝐠𝐮𝐧𝐝𝐨 parágrafo precisa começar com um “however” ou palavra similar. Você precisa demonstrar que ainda há lacunas sobre o tema que precisam ser preenchidas. Aqui é indispensável apresentar fontes muito recentes que comprovem essa lacuna. ◽ Se esses dois parágrafos estiverem bem construídos, o 𝐭𝐞𝐫𝐜𝐞𝐢𝐫𝐨 deve apr...
Leia mais

Unsupervised Machine Learning: What is, Algorithms, Example

-
Imagem
 By Prof. João Cláudio Nunes Carvalho What is Unsupervised Learning? Unsupervised Learning  is a machine learning technique in which the users do not need to supervise the model. Instead, it allows the model to work on its own to discover patterns and information that was previously undetected. It mainly deals with the unlabelled data.] Unsupervised Learning Algorithms Unsupervised Learning Algorithms  allow users to perform more complex processing tasks compared to supervised learning. Although, unsupervised learning can be more unpredictable compared with other natural learning methods. Unsupervised learning algorithms include clustering, anomaly detection, neural networks, etc. Example of Unsupervised Machine Learning Let's, take an example of Unsupervised Learning for a baby and her family dog. She knows and identifies this dog. Few weeks later a family friend brings along a dog and tries to play with the baby. Baby has not seen this dog earlier. But it recognizes man...
Leia mais
-
Imagem
  Stochastic vs Batch Gradient Descent João Cláudio Nunes Carvalho One of the first concepts that a beginner comes across in the field of deep learning is gradient descent followed by various ways in which it can be implemented. Gradient descent is one of the most important concept used in the training of neural networks for supervised learning. Hence, it is important to understand it and the different ways in which it is to be carried out on the training sets. This post mostly deals with t h e different ways in which gradient descent is implemented on a training set. Thus, I will briefly go over the definition of the concept and then explain the advantages and disadvantages of all the possible ways. Gradient Descent This is an iterative optimization algorithm for finding the minimum of a function. The algorithm takes steps proportional to the negative gradient of the function at the current point [1]. In deep learning neural networks are trained by defining a loss function and opt...
Leia mais