Machine learning is a broad discipline with several model types, subgroups, and applications. Let’s dive deeper into this article to understand what is machine learning and its use cases.
What is Machine Learning?
Machine learning is a subset of artificial intelligence that entails the study and use of algorithms and statistical models to enable computer systems to execute certain tasks without the need for human intervention. Instead of manual human training, machine learning models depend on patterns and inference. The machine learning algorithms detect patterns using SQL queries. There are multiple SQL certification courses available online that can help you understand the pattern detection process.
Machine learning can finish almost any task that can be completed using a data-defined pattern or set of rules. It enables businesses to automate operations that formerly required humans to do, such as answering customer service calls, accounting, and screening resumes.
A model must be taught to react to particular data in certain ways to extract machine center value, which necessitates a large amount of clean training data. The model will be able to do the task on actual data if it has successfully worked through the training data and understands the subtleties of the patterns it is learning.
Furthermore, let’s explore the use cases of Machine Learning.
Machine Learning Use Cases
- Customer Service Automation
Managing an ever-increasing number of online client contacts has strained many businesses. They simply don’t have enough customer service personnel on hand to handle the volume of calls they’re getting, and the traditional approach of outsourcing concerns to a contact center is just unacceptable to many of today’s customers.
Cybersecurity specialists have worked hard to adapt to the ever-increasing spectrum of security threats as networks become more complicated. It’s challenging enough to keep up with constantly evolving malware and hacking tactics, but the growth of the Internet of Things (IoT) devices has completely changed the cybersecurity environment. Attacks can occur at any moment, in any location, and in any manner so implementing machine learning can help in detecting any security breaches.
- Object Recognition
While the technology to gather and interpret data has been around for a long time, teaching computers to understand what they’re looking at has proven to be a deceptively difficult task. More and more gadgets now have object recognition capabilities thanks to machine learning algorithms.
- Fraud Detection
The growing quantity of online financial transactions has increased consumer awareness of numerous types of fraud. While people appreciate the ease of making purchases and payments online, they also want to know that their financial information is secure. Machine learning algorithms that can evaluate enormous volumes of transactional data to identify suspicious behavior have been used by credit card firms and banks as a response. Hence, using machine learning algorithms can help with fraud detection.
In every type of communication, but especially in today’s industries, avoiding mistakes and misconceptions is critical. Simple grammatical mistakes, incorrect tone, or erroneous translations can cause several difficulties in email contact, customer evaluations, video conferencing, or text-based documents in all its forms. Machine learning systems have advanced communication much beyond Microsoft’s Clippy’s heyday that can help avoid any kind of miscommunication.
The breadth of applications and use cases for machine learning will undoubtedly increase in the 2020s as technology advances. With the next decade just getting started, it’s essential keeping a watch on how machine learning use cases will be used to boost productivity, save costs, and improve user experiences.
What’s the use of Through-Hole Technology in PCB Designing?
Greetings and welcome to today’s lecture. It is going to be a very interesting and interactive class about introduction to Through Hole Technology (THT) and Surface Mount Technology (SMT) that are applied in the process of designing the printed circuit boards. A PCB board is made up of properly designed circuits that are composed of connecting wires/paths and various electrical components. The electrical components are mounted on the board. In fact, they are fixed to the board. If the components are not fixed, then there will be no durability and this might lead to various losses that can be avoided. In the process of mounting these components, here is where the through-hole technology and the surface mount technology come in. They are very important processes in the design of printed circuit boards.
This is one of the methods used in the attachment of components to PCB during the manufacturing process.
- THT is the oldest among these PCB attachment methods.
- For so long time it was the standard method that was used in the PCB assembly process.
- In the 1980s, when the surface mount technology process was introduced in the field of the PCB assembly, so many people thought that the THT method will become extinct but that is not the case.
- THT is used in all kinds of PCB designs i.e. Single Layer PCB, Multilayer PCB, Flexible PCB etc.
Through-Hole Technology (THT) is the method used in the attachment of the PCB electrical components and elements in the PCB whereby the components being placed have long leads that are soldered into the board through the holes drilled.
- Dill holes on the PCB following the clients’ design.
- Select your components. They must have long leads. Also, remember components are on the design you have been given by the client.
- Place the components on the board and ensure that their leads are on the holes as defined in the design.
- Check that the components are in the positions described in the design to ensure that there will be no errors at the end of the process.
- Solder the terminals on the board accordingly. Ensure that the solder is on one side of the leads.
- Fill the other unsoldered side with flax.
Initially, this process was done manually hence it took a lot of time before coming up with a single complete board. Today, due to the changes in technology, it has become so easy to carry out the through-hole technology process. There are several automatic systems that aid out in the process and make it easy for the manufacturers, for example, the introduction of the automated insertion machines which actually helps in inserting the electrical elements into the drilled holes in the PCB before the soldering process starts.
We have talked about the electrical components being placed on the PCB boards through the through-hole. These components can be classified into two that is the radial leads components and the axial lead components.
From the image displayed, there is already something that is building up in your mind. Observe it well. Look at the leads. Can you see something common with the device leads? Yes of course. You are right! Both the two leads originate from the common side of the components. That is what we call a radial lead component. This method finds its application commonly in the packaging of the capacitors.
The components can be mounted either vertically or horizontally.
Let us have a look at that from the images below.
The vertical mounting of the Radial THT components.
on this method, the component is always place perpendicular to the board while the base is placed parallel to the board. complete joint. Soldering is done on one side of the terminal and the other side is filled with flax.
The horizontal mounting of the Radial THT components.
the contact body is fixed on the horizontal as you can see from the images. The leads exhibit a very nice bend and also spacing. This allows the proper filling of the solder on the component hence forming the strongest
- These are the most commonly used elements of the THT PCB methods components assembly.
- Here the leads of the components appear from opposite sides to each other. See what is in the attached image on the left.
Also, it can be classified as horizontal mounting and vertical mounting.
horizontal axial mounting method
Vertical axial mounting method.
Applications of the THT
- High voltage areas eg in the medical equipment.
- High mechanical stress devices eg military equipment.
- High power areas eg in the steam boilers.
- High temperatures operating devices eg in the nuclear plants.
- Prototyping and testing of components.
- The use of the THT method will ensure that you have a very strong mechanical bond compared to the SMTs components.
- THT bound components have high resistance to wear and tear and this is made possible by the use of the large soldering deposits at the terminals.
- The THT components are very easy to swap and repair the components hence they are the best for prototyping works.
- It is best suited for places where strong mechanical applications are needed such as aerospace and military equipment.
- Due to the drilling of the required holes, the production cost goes higher compared to the other method.
- Also, drilling of the holes requires some additional time, hence the THT method takes a longer time compared to other methods.
- This method limits the available routing paths for the multilayer PCBs because the drilled holes have to go through the given layers.
- The technology being used in the industrial mass production of the THT types of the PCB is less reliable compared to the other methods used.
|THROUGH HOLE||SURFACE MOUNT|
|The components require the drilling of the holes for mounting.||No holes are required for mounting. Mounting is done through pads.|
|All the components are mounted on one side of the board and it is in most cases done manually.||Components can be mounted on either side of the board and the process is mostly automated.|
|The process of mounting is either manual or can be automated.||The mounting process is basically automated.|
|Do not employ the use of stencils.||This process involves the use of stencils to be achieved.|
|There are no vias in the pads.||Use of the vias in the pads.|
|These are used when a low density of the component is needed.||This works so well when the component density is very high.|
|Reworking and repairing are very simple.||Here the process of repairing and reworking is very complex.|
How to Choose Your Gaming PC by PC Power Up?
Computers are one of the best tools that exist to play games, we know it well. So much so, that it is one of the preferred options for many users when it comes to gaming, even above consoles. And that the latter have hardware and software focused exclusively on playing games. Here are some things to consider about PC components that are available on PC Power Up and these are tested and suggest by experts.
The graphics card (GPU):-
This element is one of the most important in a gaming PC. It delivers the power needed to display games for the graphics part and, depending on its capabilities; you can enjoy one with a higher or lower resolution. We consider that today you need at least a GTX 1660 with 6giga of RAM but for light games like Fortnite a 1650 4giga will be sufficient. For those who want to enjoy recent games with Ray Tracing at 1080p, an RTX 2060 is the minimum.
The Processor (CPU):-
The processor is essential, since all the tasks of a PC necessarily pass through it. If it’s not fast enough, you might have the best graphics card on the market; it won’t use all of its power because the CPU isn’t keeping up. A good GPU / CPU combo is very important for playing; consider a 6-core for gaming and an 8-core for multitasking. You can find more information in our review of processors for gaming.
RAM Or Memory:-
For a good PC that holds up, you need at least 8GB of RAM, but now the standard is 16 Giga. The RAM is connected to the processor; it is used to store the information which will be sent to it. Too low RAM and that’s the tragedy everything is slowed down.
The Hard Drive:-
On a gaming PC, it is strongly recommended to have at least a 256GB SSD to install Windows and games. SSDs are much faster than hard drives (HDDs). A bonus HDD allows you to store the rest of your files or several games;
Keyboard and Mouse:
Not the most important thing, but a good quality gaming keyboard / gaming mouse combo can be decisive in your games;
This is essential because without a screen, no display, it makes sense. There are a multitude of screens, but be aware that TNs are more affordable and can be of high quality as well, especially for gaming; For small budgets we will therefore opt for a TN panel screen in 1080p and ideally ultra responsive with 1ms.
The Audio System:-
It will be entirely up to you, whether you prefer to play with headphones or with speakers. In this second case, there are PC speakers to be connected, or you can take advantage of those integrated into certain screens (but the quality is often lower).
Wired Network and Wi-Fi:-
To play, it is necessarily preferable to have an Ethernet port on your motherboard. But if you cannot stretch a cable from your box to your PC, opt for a quality Wi-Fi card.
What Is Data Science And Why Has The Demand For Data Scientists Increased?
Throughout the last decade, many organizations have executed data science to get immense development in the business and have thought that it is useful. Indeed, this position has been connecting plenty of adolescents and mid-matured experts. The essential purpose of the demand for data science courses taking over different experts is to settle on data-driven choices. To run a fruitful organization in the 21st century, you need to have information that addresses your interest group and the objective market.
Thus, if you wish to be a Data Scientist and need to get familiar with this idea, this article is curated only for you. Here, you will get to know why the demand for data scientists has increased and the data scientist eligibility.
What is Data Science?
Data science is the field of applying progressed analytics strategies and logical standards to extract meaningful information from data for business dynamics, strategic planning, and different purposes. It’s undeniably helpful to organizations. The experiences that data science creates assist associations in expanding functional efficiency, distinguishing new business openings, and further developing advertising and sales programs, among different advantages. Eventually, they can prompt upper hands over business rivals.
To lay it out plainly, data science is an interdisciplinary area that utilizes logical strategies, methods, calculations, and frameworks to get information and insights from organized and unstructured data and apply that vital information to a wide assortment of use areas.
Information preparation, profound learning, and colossal information are additionally a portion of the fundamental parts of data science. Predominantly, data science is utilized to decide and forecast with the assistance of prescient causal analytics, machine learning, and AI.
These information-controlled experts have a ton to bring to the table. From assembling to friendliness, data scientists can bring priceless experiences that change the manners in which we direct business, prompting more prominent arrangements and cost-decreasing openings. While vocation development might be moved by industry and financial action, the rise of data science is on a large vertical pattern. We can see where openings might be most broadly accessible and how data scientists can take advantage of these movements by analyzing this pattern.
Data Scientist Eligibility
To establish a career as a data scientist, you should dominate some fundamental abilities such as analyzing, comprehension, and gathering information. Some other data scientist eligibility requirements are:
- You should know the tools used to analyze the data set, like Teradata, MySQL, Oracle, and Microsoft SQL Server.
- You should know fundamental numerical examinations like statistics and probability. While insights manage the review and improvement of the information and computation of the results, the probability is the estimation of conceivable outcomes. The numerical analysis comprises the fundamentals, limits, combinations, factors, integrations, values, vectors, chances, series, etc.
- Information wrangling is one more prerequisite to turning into a data scientist as it helps in cleaning, controlling, and coordinating the information.
- Data science depends on programming instruments, which are the foundation of the discipline. Expertise in at least one programming language is the primary ability of a data scientist. You can think about learning Python, R, SAS, or any other language that meets the prerequisite.
- Being a data scientist, you should have the ability to comprehend the outcome. Data perception combines various informational indexes and produces a visual portrayal of the information utilizing outlines, diagrams, and charts.
Reasons why Data Science Jobs are in Demand
1. Organisations are facing real challenges in organizing data
Throughout the IT blast of the last part of the 1990s and mid-2000s, the emphasis was on the ‘lift and shift’ of disconnected business measures into robotized PC frameworks. Over these twenty years, there has been steady electronic substance creation, conditional information age, and floods of information logs. This implies that each association is currently sitting on a heap of information that it knows can be of rich worth but doesn’t have the ability. Data Science Jobs is in the best position for the second year straight with a score of 4.8/5.
2. Significant pay development in Data Science and Machine Learning
As associations are turning towards Machine Learning (ML), Big Data, and Artificial Intelligence, the interest for data science jobs is seeing maintenance and speeding up the vertical flood. Starting around 2012, the Data Science area has seen a significant climb of 650%, dominating different regions. Accordingly, progressing to data science is a savvy move as it gets far higher near returns. For example, changing from a promoting investigation occupation to a data science work prompts a 37% compensation improvement.
Also, the standard compensation development when individuals change from digital analytics to data science is 31% by and large. For somebody progressing from a data engineering job to a data science job, the compensation climb is pretty high.
3. Irreplaceable repute
Being a Data Scientist is hailed as being unquestionably excellent with top data scientists working at Google, Linked In, Facebook, Amazon, and Twitter. It is no big surprise that the Harvard Business Review marked Data Scientist as ‘the hottest occupation of the 21st century. The obligations of a Data Scientist are excellent and novel to the work job. The idea helps them to progress in their profession, joining numerous insightful abilities over different spaces—for example, AI, tremendous information, and so forth. This vast pool of information furnishes them with an indispensable reputation.
4. Everyone can pursue
Since enterprises from assembling to medical services, IT to banking are utilizing data science to a limit, there is no shortage of Data Science Jobs for any intrigued individual and will buckle down. This isn’t simply restricted to businesses but also across different topographies. Therefore, independent of somebody’s topographical position or current space, data analytics and science is open for everybody to seek after.
5. Many other sub-roles are available
While Data Science Jobs is an all-encompassing term, inside its more considerable significance, numerous other sub-jobs are accessible. Jobs, such as that of a Data Scientist, Data Architect, BI Engineer, Business Analyst, Data Engineer, Database Administrator, Data Analyst and Analytics Manager can be chosen in the data science field.
Although data science is another field, it permits passage to various experts from various foundations. Numerous current Data Scientists hail from arithmetic or statistics, software engineering, designing, and other science disciplines. Some even have degrees in financial matters, sociology and business. They have all figured out how to encourage a critical thinking soul and have upskilled themselves on the web or through formal courses.
With the worth of data science clear in the capability of many enterprises, data science will be developing for quite a long time to come. As the openness and force of data become more regular, so too does the requirement for data scientists.
Even though there is an enormous convergence of data scientists, consistently, not many individuals have the necessary aptitude and specializations, there is a flooding interest for experts with specific data abilities. Depending on where you are in terms of knowledge, you can select programs or courses that offer you a complete learning experience. You can pursue a Master’s in Data Science for working professionals to further your career in Data Science and related fields. Great Learning offers this course in online mode for your ease and convenience.
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