Vu's Blog

Agent : The agent is the software program that learns to make intelligent decisions, such as a software program that plays chess intelligently. Environment : The environment is the world of the agent. If we continue with the chess example, a chessboard is the environment where the agent plays chess. State : A state is a position or a moment in the environment that the agent can be in. For example, all the positions on the chessboard are called states. Action : The agent interacts with the environment by performing an action and moves from one state to another, for example, moves made by chessmen are actions. Reward : A reward is a numerical value that the agent receives based on its action. Consider a reward as a point. For instance, an agent receives +1 point (reward) for a good action and -1 point (reward) for a bad action. Action space: The set of all possible actions in the environment is called the action space. The action space is called a discrete action space when our action...

2 Methology convert text data into data structure (vector and matrix) 👉  Bag of Word (BoW): Evaluation the frequency of the words in that particular document. Sentence can be represented as a vector with length would be equal to the size of vocabulary. CountVectorizer is python libarary conveniently help in building BoW model. Limitations of the BoW: work well for certain tasks or use cases with a limited vocabulary, not scale to large vocabularies efficiently. 👉  TF-IDF vectors: Approach with weigh terms, vectorizing text and extracting features out of it. TF : account how frequently a term occurs in a document. IDF : justice to terms that occur not so frequently across documents. TF-IDF is computationally fast however does not take into account co-occurrence of terms, semantics, the context associated with terms. Both method use Cosine to evaluation how similar or dissimilar text documents. 

4  Interesting Deep Learning Algorithms 1. Artificial Neural Networks (ANNs) 👉 With 3 Layers - Input layer : No computation is performed,  just used for passing information from the outside to the network. - Hidden layer : Deriving complex relationships between input and output. Identifies the pattern in the dataset, learning the data representation and for extracting the features. We cloud use many hidden layers, each layer is responsible for extracting important features. - Output layer:  Number of neurons in the output layer is based on the type of problem we want our network to solve (Example: binary classification, number of neurons in the output layer is one).  ⏩ Other Concept: - Activation functions ( ex: sigmoid, tanh, ReLU, softmax ): To introduce a non-linear transformation to learn the complex underlying patterns in the data. - Cost function:  Use Optimization Algorithms (Gradient descent) to minimize cost so that Network predictions will b...

👉 Raid (Redundant Array of Independent Disks): Redundant solution because it allows data to be written to multiple hard disks at the same time. In addition, RAID has many variations that allow to significantly increase the speed of data retrieval from the hard disk, example:  RAID 1 consists of an exact copy (or mirror) of a set of data on two or more disks; 👉 Storage pool : capacity aggregated in a shared storage environment from disparate physical storage resources. 👉 Storage volume : an identifiable unit of data storage. Although a volume might be different from a physical disk drive, it can still be accessed with an operating system's logical interface.  👉  Pwwn (port world wide name): a unique identifier for each Fiber Channel port presented to a Storage Area Network (SAN) 👉    iRMC : Integrated Remote Management Controller. 👉  iDRAC   (The Integrated Dell Remote Access Controller) designed for secure local and remote server management ...

Service level agreement (SLA): responsible for a set of agreements between a service provider and customer that define the scope, quality and speed of the services being provided. Operational Level Agreement (OLA): an internal agreement that outlines how different departments and teams will support the delivery of services to your clients. OLA SLA Internal-facing between MSP teams and departments External-facing between the MSP ( managed service provider   ) and the client Provide operational workflows and guidelines for collaboration Define the level of service expected by the client Outline key responsibilities, dependencies, and relationships Offer key metrics and KPIs for uptime, response time, resolution time, and availability Affect internal operations and daily efficiency Affects the overall client experience and satisfaction Keep teams in...