Art of Negotiation for Your Service
Developing a Sales Focused Mindset Handle the initial meeting with the client You have joined the scheduled meeting (e.g Zoom call.) with the client and don’t find anyone in the meeting. Don’t see any message from the client about the delay. Don’t wait for than 3 mins in that call. Disconnect the call and drop […]
Pandas & Numpy
NumPy NumPy (or Numpy) is a Linear Algebra Library of Python Almost all libraries in the PyData Ecosystem rely on Numpy as one of their main building blocks Numpy is incredibly fast, as it has binding to C libraries Numpy arrays have two flavours: Vectors and Matrices Vectors are strictly 1D arrays and matrices are […]
Prompt Engineering
Engineering Your Prompts Ask GPT to simulate a professional Before asking the question, we must switch GPT to someone relevant to our problem statement. e.g If I need some maths advice, I’d ask GPT to ‘act as a math professor’ to be more precise ‘act as mathematics professor who specialises in discrete mathematics’ This is […]
Chatbot
Key terms for chatbot UX design Intent: Intent is a user’s purpose for interacting with your chatbot—the specific goal or problem to address, like paying a bill or getting a question answered. Utterance: An utterance is any individual statement made during an exchange, like “hello!” or “I’d like to pay my bill” or “yes.” Exchange: An exchange consists […]
Vector Database
Why Vector Database? AI applications handle a vast amount of data. And for advanced AI applications e.g. image recognition, voice search, fraud detection or recommendation engine, the vastness of the data further increases. Vector DB is used to handle such vast and intricate data. It enable users to use semantics searches to find an object. […]
Test Latex
At first, we sample in the ( is odd) equidistant points around :[ f_k = f(x_k),: x_k = x^*+kh,: k=-frac{N-1}{2},dots,frac{N-1}{2}]where is some step.Then we interpolate points by polynomialbegin{equation} label{eq:poly} P_{N-1}(x)=sum_{j=0}^{N-1}{a_jx^j}end{equation}Its coefficients are found as a solution of system of linear equations:begin{equation} label{eq:sys} left{ P_{N-1}(x_k) = f_kright},quad k=-frac{N-1}{2},dots,frac{N-1}{2}end{equation}Here are references to existing equations: (ref{eq:poly}), (ref{eq:sys}).Here is reference to non-existing equation (ref{eq:unknown}). […]
AI ML DL – Basic
Computer Vision CV is around since 1950 e.g Bar code scanner. Two types of Computer Vision Algorithm – Classical CV: Relies on prebuilt libraries of features.It collect images and label them according to similar characteristics & group them in dataset or library of features. Example : Sorting good and bad tomatoes. Pros – Algorithm work […]
Basic Statistics
Formulas 1. Pearson’s first coefficient of skewness, or Pearson mode skewness begin{equation} label{eq:stat1} S_k1 = frac{(bar{X} – M_o)}{sigma}end{equation} 2. Pearson’s second coefficient of skewness, or Pearson median skewness begin{equation} label{eq:stat2} S_k2 = frac{3*(bar{X} – Med)}{sigma}end{equation} : Mean : Mode : Median : Standard Deviation Common Terminologies Data or Raw Data or Ungrouped Data Two […]
LLM
What is the Large Language Model (LLM)? LLM is a Deep learning algorithm. LLM largely represent a class of Deep Learning architecture called Transformer models/networks. The transformer model is a neural network that learns context and meaning by tracking relationships in sequence data, like the words in the sentence. Two key innovations make transformers particularly […]
Convolutional Neural Network (CNN or ConvNet)
What are Convolutional Neural Networks (CNNs)? Area of Deep Learning specializes in pattern recognition. e.g. when we draw the picture of an object it identifies what object it is. The network consists of multiple layers that are interconnected, and each layer receives some input, transforms that input to something else, and passes it as output […]