Data science class-008

 

• Supervised Learning: Supervised learning learns from a set of labeled data. It is an algorithm that predicts the outcome of new data based on previously known labeled data.
• Unsupervised Learning: In unsupervised machine learning, training is based on unlabeled data. In this algorithm, you don’t know the outcome or the label of the input data.
• Semi-Supervised Learning: The AI will learn from a dataset that is partly labeled. This is the combination of the two types above.
• Reinforcement Learning: Reinforcement learning is the algorithm that helps a system determine its behavior to maximize its benefits. Currently, it is mainly applied to Game Theory, where algorithms need to determine the next move to achieve the highest score.

Data annotation for machine learning is the process of labeling or tagging data to make it understandable and usable for machine learning algorithms. This involves adding metadata, such as categories, tags, or attributes, to raw data, making it easier for algorithms to recognize patterns and learn from the data.

In fact, data annotation, or AI data processing, was once the most unwanted process of implementing AI in real life. Data annotation AI is a crucial step in creating supervised machine-learning models where the algorithm learns from labeled examples to make predictions or classifications.

1) Cloud Computing -advantages - On Demand , Low Capex

 VMs

 Hypervisor

VM -> Containers 

Microservices 

github repo 

usage: git [-v | --version] [-h | --help] [-C <path>] [-c <name>=<value>]

           [--exec-path[=<path>]] [--html-path] [--man-path] [--info-path]

           [-p | --paginate | -P | --no-pager] [--no-replace-objects] [--bare]

           [--git-dir=<path>] [--work-tree=<path>] [--namespace=<name>]

           [--config-env=<name>=<envvar>] <command> [<args>]

These are common Git commands used in various situations:

start a working area (see also: git help tutorial)

   clone     Clone a repository into a new directory

   init      Create an empty Git repository or reinitialize an existing one

work on the current change (see also: git help everyday)

   add       Add file contents to the index

   mv        Move or rename a file, a directory, or a symlink

   restore   Restore working tree files

   rm        Remove files from the working tree and from the index

examine the history and state (see also: git help revisions)

   bisect    Use binary search to find the commit that introduced a bug

   diff      Show changes between commits, commit and working tree, etc

   grep      Print lines matching a pattern

   log       Show commit logs

   show      Show various types of objects

   status    Show the working tree status

grow, mark and tweak your common history

   branch    List, create, or delete branches

   commit    Record changes to the repository

   merge     Join two or more development histories together

   rebase    Reapply commits on top of another base tip

   reset     Reset current HEAD to the specified state

   switch    Switch branches

   tag       Create, list, delete or verify a tag object signed with GPG

collaborate (see also: git help workflows)

   fetch     Download objects and refs from another repository

   pull      Fetch from and integrate with another repository or a local branch

   push      Update remote refs along with associated objects

'git help -a' and 'git help -g' list available subcommands and some

concept guides. See 'git help <command>' or 'git help <concept>'

to read about a specific subcommand or concept.

See 'git help git' for an overview of the system.