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An influencer trains to become a lucid dreamer to battle against an evil force in her nightmare.<br/><br/>\
⏲ 17:8 👁 315K
Simple Nursing
⏲ 6 minutes 59 seconds 👁 158.7K
RegisteredNurseRN
⏲ 10 minutes 44 seconds 👁 717.9K
Yulia Gerasimova is a notable Ukrainian volleyball player known for her skills and achievements in the sport. Here are some key points about her:<br/><br/>1. **Position**: Yulia typically plays as a middle blocker, a crucial position responsible for both offensive and defensive plays at the net.<br/><br/>2. **Career Highlights**: Throughout her career, she has been recognized for her powerful spikes, blocks, and overall court presence. She has competed in various national and international tournaments, representing Ukraine.<br/><br/>3. **Teams**: Yulia has played for several clubs in different leagues, contributing significantly to their successes. Her club career has seen her participate in top-tier volleyball competitions.<br/><br/>4. **National Team**: As a member of the Ukrainian national team, Yulia has represented her country in numerous international competitions, showcasing her talent on a global stage.<br/><br/>5. **Physical Attributes**: Like many volleyball players, Yulia has an impressive height and athletic build, which aids her performance as a middle blocker.<br/><br/>6. **Impact on Volleyball**: Yulia Gerasimova is admired for her dedication, sportsmanship, and the example she sets for aspiring volleyball players in Ukraine and beyond.<br/><br/>These points highlight Yulia Gerasimova's contributions and significance in the world of volleyball. If you need more specific information or details about her career statistics, feel free to ask!
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Beautiful Nursing
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Level Up RN
⏲ 15 minutes 57 seconds 👁 53.6K
Welcome to Session 14 of our Open RAN series! In this session, we'll introduce supervised machine learning and its application in designing intelligent systems for Open RAN.<br/><br/><br/>Understanding Supervised Machine Learning:<br/>Supervised machine learning is a type of machine learning where the algorithm learns from labeled data. It involves training a model on a dataset that contains input-output pairs, where the input is the data and the output is the corresponding label or target variable. The algorithm learns to map inputs to outputs by finding patterns in the data. In Open RAN, supervised learning can be used for tasks such as predicting network performance based on historical data.<br/><br/>Types of Supervised Machine Learning:<br/>There are two main types of supervised machine learning: classification and regression. In classification, the algorithm learns to categorize data into predefined classes or categories. For example, it can classify network traffic into different application types (e.g., video streaming, web browsing). Regression, on the other hand, involves predicting continuous values or quantities. It is used when the output variable is a real or continuous value, such as predicting the signal strength of a network connection.<br/><br/>Binary and Multi-Class Classification:<br/>Binary classification involves categorizing data into two classes or categories. For example, it can be used to classify network traffic as either malicious or benign. Multi-class classification, on the other hand, involves categorizing data into more than two classes. It can be used to classify network traffic into multiple application types (e.g., video streaming, social media, email).<br/><br/>Regression in Machine Learning:<br/>Regression is a supervised learning technique used for predicting continuous values or quantities. It involves fitting a mathematical model to the data, which can then be used to make predictions. In Open RAN, regression can be used for tasks such as predicting network latency, throughput, or coverage based on various input variables such as network parameters, traffic patterns, and environmental conditions.<br/><br/>Subscribe to \
⏲ 4:28 👁 40K
That nursing prof
⏲ 26 minutes 56 seconds 👁 57.1K
Lecturio Nursing
⏲ 5 minutes 56 seconds 👁 1.7K
The electric motor on the rear axle is particularly powerful due to its 6-phase operation: it has two windings with three phases each.<br/><br/>To recuperate, the driver does not need to press the brake pedal; literally 1-pedal driving. Thanks to ECO Assist, the EQE SUV also decelerates automatically to a standstill when it detects vehicles ahead, for example at traffic lights.<br/><br/>The charging system is located above the rear axle of the EQE SUV. It can be used to charge the battery from the public mains with single-phase or three-phase alternating current and an optional charging capacity of up to 22 kW.<br/><br/>Mercedes-Benz issues a battery certificate for its high-voltage batteries, and thus a performance guarantee to customers: 10 years or a mileage of 250,000 kilometres with a defined residual capacity.<br/><br/>The chassis of the new EQE SUV comprises a four-link suspension at the front and an independent multi-link suspension at the rear. Thanks to the comparatively short wheelbase of 3030 millimetres and the corresponding suspension tuning, it feels particularly agile and manoeuvrable even with the basic set-up.<br/><br/>The AIRMATIC air suspension with ADS+ continuously adjustable damping is available as an optional extra. To increase ground clearance, the vehicle level can be raised by up to 30 millimetres. Rear-axle steering with a maximum steering angle of 10 degrees is available as an option.
⏲ 1:52 👁 55K
Ina Irabon
⏲ 22 minutes 32 seconds 👁 57.5K
NURSINGcom w/Jon Haws, RN
⏲ 2 minutes 15 seconds 👁 45.6K
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