There are a lot of basic things to learn before you are able to use Scala efficiently. In this Video you learn most of the Scala basic features. I used Scala 2 for this video.
Getting Started: (00:00:21)
Variables & Types: (00:01:58)
String Interpolation: (00:10:06)
If Statement: (00:11:53)
Do-While & While-Loop: (00:13:20)
Using Java Libraries: (00:18:35)
Functions & Lambdas : (00:19:36)
Collections (Lists & Maps): (00:33:51)
Traits & Classes with Extentions & Mixin : (00:45:40)
Compound Types: (00:51:18)
Nested Classes: (00:53:26)
Case Classes: (00:54:46)
Singleton Objects: (00:57:36)
Functions as Objects: (00:58:50)
Implicit Classes: (01:04:41)
Pattern Matching: (01:09:51)
The gaming industry has taken a boom in the last few years. If we talk about numbers, according to NewZoo, the worth of the video gaming industry was $159.3 Billion in 2020. Video games are not just something for fun now, players and users expect much more from video game developers. Creating such products that just do not satisfy the player’s needs and exceed their expectations is what video game development company are thriving for.
Though kickstarting a new game-making studio is not an easy task. This business requires a team with a huge passion to create games and earn money from these video games. The idea of the approach is to create such unique games that will reach millions of people in the world and gain popularity. This growth demands more professionals in this field.
This just can not be obtained by finding someone with a good CV, the whole process includes a deep dig down to grab the right talent. Read on to learn more about Mobile game developers and the process of hiring video game developers.
Read Complete Blog Here - https://theninehertz.com/blog/how-to-hire-video-game-developers-video-game-development
#Video Game Development
#Video Game developers
#Video game development studio
#Video game development services
A video calling feature can be easily integrated into any existing application, allowing to leverage the functionality in order to improve productivity. This is a great idea for saving money and development time. To do so all we need to do is integrate the API or SDK for video calling into the existing software.
In the rapidly modernizing world, technology has advanced in a hurtle. The use of mobile gadgets has surged a lot. The world is growing digital and everything is accessible from a single place. In the company of modernization, there is a huge increase in digitalization. Virtual communication has been nowadays an important tool to keep up with people. Due to virtual video communication, we can today talk face-to-face overseas too. Such a great invention to make work easy.
Many companies work on the aspect of virtual communication. The video calls we do to communicate with our clients, corporates, and family are developed with the help of Software Development Kits (SDKs). Companies align with competition and design their SDKs to support their video calling applications and websites. These days conferencing has become so efficient without any lags or errors or issues. This is just because of the effective product delivery of the companies who have landed themselves to make an effective approach towards real-time communication.
Video Calling API are app development kits that complement apps that support video calling features on their applications to connect their customers with the community. These SDKs are developed by companies with their effective creative SDK ideas, built with interfaces designed in a lucrative way to make them attract users.
The rise in remote working has also led to a rise in video conferencing in companies in both internal and external environments. To detail a video SDK, let us understand the significance to develop a clear idea of how SDK works. Video conferencing is considered to be one of the most important tools for business considering the pandemic situation, video SDK makes it efficient.
Video Calling API makes efficient use of resources. It helps to lower the costs in many direct and indirect ways. The tangible costs are cut. The designed SDKs help in eliminating costs with their integrated functions.
Video Calling API helps in faster delivery, saving a lot of time. They help in creating video conferences for businesses with their integrated.
Video Calling API are a stable platform build-up for apps with video conferencing. They make video conferencing flexible and accessible from any place and any time.
Video SDK allows conferencing on a large scale helping businesses achieve their desired objectives.
Video conferencing has become significant over time and for that reason, a strong SDK build-up is now an urge for each company. Being the product providers, the companies who build these SDKs look to deliver all their innovations in it so that the end customer finds it very much involved and attractive. An ideal Video SDK must have these features.
The very basic feature a Video SDK must have is an effective video conferencing interface. It must be compatible for one-to-one communication as well as communication on a mass scale. This is the foremost feature to address while choosing a video-conferencing application.
A video conferencing application must be designed to provide real-time chats in an ongoing meeting. This helps to supplement clarity during the meeting virtually, through multimedia channels.
In an ideal video conferencing, the users generally believe to have a backup of that communication for the future. This is the top-notch requirement for a company to build up a stable domain.
A screen share enables viewing access to the participants of the meeting, developing a clear perspective of ideas thought to the ideas delivered.
An attractive Video SDK must support enabling notifications while the conference to make discussions acknowledged at the right time. This helps in running a business conference smoothly.
A video SDK must provide effective scalability so that it can be addressed with any supportive device without a screen of less clarity. It must be flexible enough to support all the devices for its accessibility.
In the market of real-time communication, various companies offer customizable video SDK interfaces for their clients. Due to the current pandemic situation, the real-time communication industry has increased a lot. People have made virtual communication as the most used method to communicate, rather it is their professional or personal life. Many companies have launched their Video SDKs with customizable features.
Video SDK is a web-RTC company that looks into creating lucrative Video SDKs and APIs for their clients. It looks for better engagement of their clients by supporting them with providing the best products for the end-users. Video SDK production, delivering sub 100ms to 150ms low latency streaming in the real-time community creating its image as the ideal platform for video conferencing due to its flexible and scalable SDKs. They aim at delivering some of the best experiences to their clients with their customizable SDKs.
Zujonow is a company that develops its product on cutting-edge technologies. It delivers products for its clients based on video conferencing with effective scalability and customizable SDKs. They also deal in products like live streaming, on-demand videos, and real-time communication. Zujonow work is a well-crafted platform for education and other related industries.
EnableX works on the development of communication APIs. it focuses on communication solutions and provides services in real-time communication for its clients. It delivers its products with SMS and chat interfaces too. EnableX works on developing educational APIs for students and also maintaining portfolios.
Daily.co is a real-time audio and video API developer, working on focusing on the best scalable video conferencing api for its clients. Daily.co works on developing global infrastructure delivering the best call quality on a timely basis, considering their web-RTC to be a source of service to the clients.
Eyeson masters into high-performing API including managed hosting and scaling for web-based business workflows on any device. It has a patented single Stream Technology merges any live media, data and participants in real-time into a single video and audio stream. The cloud services at eyeson can immediately be used for world wide scaling. It provides a world-class facility for its clients with guaranteed privacy.
Twilio develops video applications that are fully customizable, scalable, and flexible for usage. It constructs applications and connectivity and has its build-up. It makes channels for video, chats, and programmable chats. Twilio also looks at SMS build-up for its clients. It provides solutions based on real-time communication and scalability and video calling api
Pubnub is an in-app chat for real-time chat engagement. It retains full control, functionality, and customization without the time and expense of building in-house. It provides outsourcing to clients with the products like custom chat, effortless scalability, in-class integrations, and Chat UI support. They have a strong research window that looks for developing APIs for their clients.
Cometchat is designed for providing APIs and SDKs for various solutions for ed-tech, healthcare, dating, and social community. It is also devised for on-demand videos and live streaming. It allows its users to customize their Whitelabel as per their needs to make it feel like ownership. Cometchat is adaptive to all languages and has effective work data too.
Sinch works on managing different APIs for messaging and calling. It puts forward the products for video calling, voice calls, SMS verification, and other engagement platforms. It provides solutions to different industries like health, retail, telecommunications, media and entertainment, and more. It provided operators opportunities for monetizing wholesale, preventing fraud, and other activities.
Apphitect focuses on mobile app development for android and iOS. It also engages its clients with different solutions concerning messaging. Apphitect delivers app testings and mobile. It develops everything from wireframe to pixel. Apphitact is currently working in 40+ cities with its headquarters in UAE.
Vidyo provides solutions to services like Branding and white-labeling and hybrid cloud expansion. It also works with solutions for deployment services and project management services. It works for several industries like health, education, government, finance, retail; and more. It promotes connectivity and engagement for the users and also focuses on video conferencing systems for businesses.
Due to the current pandemic, real-time communication has took a massive hype for its flexible availability. All the businesses, corporates, schools, and organisations had to run over the web. Even earlier video conferencing was an all time favorable option for corporates to abide with communicating with clients, over a distance. But in the latter period, recently, the whole world has become dependent on it. For the same cause, it led to emergence of various innovative ideas for bringing people closer together even at a distance. Video conferencing has today become vital and above all it is appreciable for the companies who have invested in bringing up ideas by developing customisable video SDKs for their clients to promote belongingness. The APIs and SDKs designed by the companies have made it easier to use by the end consumers too. Overall, video conferencing makes work flexible and accessible to all, making itself categorise into an principal element of businesses.
#video-conferencing-api#video-sdk #videoapi #video-conferencing #video-sdk-comparison #video-calling-api
In this post, we will investigate how easily we can train a Deep Q-Network (DQN) agent (Mnih et al., 2015) for Atari 2600 games using the Google reinforcement learning library Dopamine. While many RL libraries exist, this library is specifically designed with four essential features in mind:
_We believe these principles makes __Dopamine _one of the best RL learning environment available today. Additionally, we even got the library to work on Windows, which we think is quite a feat!
In my view, the visualization of any trained RL agent is an absolute must in reinforcement learning! Therefore, we will (of course) include this for our own trained agent at the very end!
We will go through all the pieces of code required (which is** minimal compared to other libraries**), but you can also find all scripts needed in the following Github repo.
The general premise of deep reinforcement learning is to
“derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations.”
- Mnih et al. (2015)
As stated earlier, we will implement the DQN model by Deepmind, which only uses raw pixels and game score as input. The raw pixels are processed using convolutional neural networks similar to image classification. The primary difference lies in the objective function, which for the DQN agent is called the optimal action-value function
where_ rₜ is the maximum sum of rewards at time t discounted by γ, obtained using a behavior policy π = P(a_∣_s)_ for each observation-action pair.
There are relatively many details to Deep Q-Learning, such as Experience Replay (Lin, 1993) and an _iterative update rule. _Thus, we refer the reader to the original paper for an excellent walk-through of the mathematical details.
One key benefit of DQN compared to previous approaches at the time (2015) was the ability to outperform existing methods for Atari 2600 games using the same set of hyperparameters and only pixel values and game score as input, clearly a tremendous achievement.
This post does not include instructions for installing Tensorflow, but we do want to stress that you can use both the CPU and GPU versions.
Nevertheless, assuming you are using
Python 3.7.x, these are the libraries you need to install (which can all be installed via
tensorflow-gpu=1.15 (or tensorflow==1.15 for CPU version) cmake dopamine-rl atari-py matplotlib pygame seaborn pandas
#reinforcement-learning #q-learning #games #machine-learning #deep-learning #deep learning
In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own.
If you already know how to use RStudio and want to learn some tips, tricks, and shortcuts, check out this Dataquest blog post.
[tidyverse](https://www.dataquest.io/blog/tutorial-getting-started-with-r-and-rstudio/#tve-jump-173bb264c2b)Packages into Memory
#data science tutorials #beginner #r tutorial #r tutorials #rstats #tutorial #tutorials
What exactly is clean data? Clean data is accurate, complete, and in a format that is ready to analyze. Characteristics of clean data include data that are:
Common symptoms of messy data include data that contain:
In this blog post, we will work with five property-sales datasets that are publicly available on the New York City Department of Finance Rolling Sales Data website. We encourage you to download the datasets and follow along! Each file contains one year of real estate sales data for one of New York City’s five boroughs. We will work with the following Microsoft Excel files:
As we work through this blog post, imagine that you are helping a friend launch their home-inspection business in New York City. You offer to help them by analyzing the data to better understand the real-estate market. But you realize that before you can analyze the data in R, you will need to diagnose and clean it first. And before you can diagnose the data, you will need to load it into R!
Benefits of using tidyverse tools are often evident in the data-loading process. In many cases, the tidyverse package
readxl will clean some data for you as Microsoft Excel data is loaded into R. If you are working with CSV data, the tidyverse
readr package function
read_csv() is the function to use (we’ll cover that later).
Let’s look at an example. Here’s how the Excel file for the Brooklyn borough looks:
The Brooklyn Excel file
Now let’s load the Brooklyn dataset into R from an Excel file. We’ll use the
readxlpackage. We specify the function argument
skip = 4 because the row that we want to use as the header (i.e. column names) is actually row 5. We can ignore the first four rows entirely and load the data into R beginning at row 5. Here’s the code:
library(readxl) # Load Excel files brooklyn <- read_excel("rollingsales_brooklyn.xls", skip = 4)
Note we saved this dataset with the variable name
brooklyn for future use.
The tidyverse offers a user-friendly way to view this data with the
glimpse() function that is part of the
tibble package. To use this package, we will need to load it for use in our current session. But rather than loading this package alone, we can load many of the tidyverse packages at one time. If you do not have the tidyverse collection of packages, install it on your machine using the following command in your R or R Studio session:
Once the package is installed, load it to memory:
tidyverse is loaded into memory, take a “glimpse” of the Brooklyn dataset:
glimpse(brooklyn) ## Observations: 20,185 ## Variables: 21 ## $ BOROUGH <chr> "3", "3", "3", "3", "3", "3", "… ## $ NEIGHBORHOOD <chr> "BATH BEACH", "BATH BEACH", "BA… ## $ `BUILDING CLASS CATEGORY` <chr> "01 ONE FAMILY DWELLINGS", "01 … ## $ `TAX CLASS AT PRESENT` <chr> "1", "1", "1", "1", "1", "1", "… ## $ BLOCK <dbl> 6359, 6360, 6364, 6367, 6371, 6… ## $ LOT <dbl> 70, 48, 74, 24, 19, 32, 65, 20,… ## $ `EASE-MENT` <lgl> NA, NA, NA, NA, NA, NA, NA, NA,… ## $ `BUILDING CLASS AT PRESENT` <chr> "S1", "A5", "A5", "A9", "A9", "… ## $ ADDRESS <chr> "8684 15TH AVENUE", "14 BAY 10T… ## $ `APARTMENT NUMBER` <chr> NA, NA, NA, NA, NA, NA, NA, NA,… ## $ `ZIP CODE` <dbl> 11228, 11228, 11214, 11214, 112… ## $ `RESIDENTIAL UNITS` <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1… ## $ `COMMERCIAL UNITS` <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0… ## $ `TOTAL UNITS` <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1… ## $ `LAND SQUARE FEET` <dbl> 1933, 2513, 2492, 1571, 2320, 3… ## $ `GROSS SQUARE FEET` <dbl> 4080, 1428, 972, 1456, 1566, 22… ## $ `YEAR BUILT` <dbl> 1930, 1930, 1950, 1935, 1930, 1… ## $ `TAX CLASS AT TIME OF SALE` <chr> "1", "1", "1", "1", "1", "1", "… ## $ `BUILDING CLASS AT TIME OF SALE` <chr> "S1", "A5", "A5", "A9", "A9", "… ## $ `SALE PRICE` <dbl> 1300000, 849000, 0, 830000, 0, … ## $ `SALE DATE` <dttm> 2020-04-28, 2020-03-18, 2019-0…
glimpse() function provides a user-friendly way to view the column names and data types for all columns, or variables, in the data frame. With this function, we are also able to view the first few observations in the data frame. This data frame has 20,185 observations, or property sales records. And there are 21 variables, or columns.
#data science tutorials #beginner #r #r tutorial #r tutorials #rstats #tidyverse #tutorial #tutorials