Working From Home – Survival Tips From Molly

If you know me, you’ll know that I am a person that needs people — I have often referred to myself as ‘short attention span,’ as constant human interaction and distraction is needed for me to function.

Although I survived Day 1 of WFH (working from home), I can tell you it wasn’t easy. Starting out on Day 2, I have compiled a list of items that will (hopefully) get me through the next few weeks and may even help others as well!

  1. Keep your routine. I normally wake up between 4:00 – 4:30 am and start the day. Clearly, I don’t work out — but I do consume loads of coffee, review the emails that came in overnight, and watch the news on TV.
  2. Don’t change your work start time. I typically leave the house by 6 am, so now that there is zero commute time, I come into my home office and start my day at 6:30 (and just think of all the extra coffee I can consume during the non-commute!).
  3. STAY CONNECTED! During the workday, stay in contact with co-workers and management. Since this is shaping up to be the ‘new normal,’ in order to be effective in your job you will need to collaborate with others… whether it be a phone call, email, or a chat session with team members.
  4. Focus. Being at home has its distractions, like a garbage truck going by, dogs barking, or a bird fluttering outside your window. Regardless of the distraction, it is important to focus on your job. What works for me is compiling a daily list of ‘need to get done today’ items. Although work-related distractions will inevitably happen (the impromptu meetings or screen shares), you will at least have your daily short list of items to bring you back to the tasks at hand.
  5. Lunch. I am not a lunch (or breakfast, for that matter) person, but being at home and knowing that there is food available makes me want to eat lunch! It isn’t all bad, though. Getting away from your desk for the 15 or so minutes is a great way to clear your mind and feed your belly. And if you throw a load of laundry in at that time? Score!
  6. Setting your end time. The beauty of working from home is not having to travel, and without the commute I always feel that I can work a little longer and get more done. That is a perk, but don’t go crazy. By that, I mean if you hear the 10 pm news from another room, you may want to cut back a bit. Set an alarm on your phone for your ‘ideal’ end time… for me, it is set for 7 pm.

That’s it. Hopefully these tips will help you, as well as help me, get through these somewhat challenging times. In the meantime, stay safe, wash your hands, and get to work!!

Coronavirus Driving People From The Stock Market

The coronavirus’ stock market impact is immense. It is spooking stock markets. The Dow Jones Industrial Average (DJIA) shed 12% or over 3000 points over five days, February 24-28, the largest 5-day drop since the Great Recession. The DJIA recorded the biggest single day drop (1191) during that week on February 27.

China is a key player in companies’ supply chain. That’s why analysts fear firms in China won’t deliver parts to companies like Apple and Walmart, which will cause these firms’ results to suffer. The fear of the unknown is causing panic. Stock markets hate uncertainty, and this virus comes with an abundance of uncertainty: When will there be a vaccine? How will countries contain it, and so on?

Coronavirus’ Stock Market Impact Could Linger

Nobody knows how long the coronavirus’ stock market impact will last. But history shows us that stock markets over-react and then continue their upward momentum. Today, the rapid proliferation of the virus increases fear, so people are over-reacting. We need to pause and not rush to the exit.

Markets recovered quickly from past viral outbreaks. Will the coronavirus’ stock market impact lead to a realized capital loss to you? The market change, per se, does nothing. You lose funds only when you sell below market price. Some firms’ results will suffer in the short-to-medium term because of insufficient inventory. Other companies will gain. Although we do not know the virus’ severity, judging from past market responses, caution is the key response.

Are you a value investor with targeted companies in your portfolio? Examine your goals and stay the course unless you see changes in the firm’s intrinsic value. Have you been speculating, looking to make a quick buck with a margin account? If so, you will have a challenge because banks will call your margin. That’s the inherent risk when you use a margin account to speculate.

If you are not a speculator but a value investor, now could be the perfect time to identify value stocks and select those at bargain prices. There will be several. Whoever you are, be cautious, reject the herd mentality, and reflect on these matters:

Stay The Course

  1. Review or develop an investment goal and plan before you adjust your portfolio. Why have you been or do you wish to invest? Your reason will decide your investment strategy. My preferred strategy is to buy blue chip equities with a long history of increasing dividends. I hold these shares, review their fundamentals from time to time, and act when there is a permanent change.
  2. You will find value stocks today. Market fluctuations provide a great opportunity to buy solid companies with good track records. Remember, you lose, or gain on sale only, not when markets fluctuate.
  3. When your investments’ intrinsic value change, confirm your strategy, and sell your holdings, even at a loss; don’t time the market recovery. The market could be down for several years like the Tokyo Stock Market, which has been below its bubble heights for over two decades.
  4. Don’t let generic asset mixes influence your asset allotment between stocks, bonds, cash, commodities. You are unique, and your mix should fit you at your life stage. Think before rushing to so-called safe-haven commodity assets such as gold that has no intrinsic value.
  5. If you are in the retirement red zone, five to seven years to retirement, your goal must be capital preservation, so avoid the stock market.
  6. Don’t panic: focus on your goals, plan, long-term strategy. Update these and ensure they fit your needs and your risk profile.
  7. This, too, will pass, but God alone knows the timing.

Michel A. Bell is author of six books including Business Simplified, speaker, adjunct professor of business administration at Briercrest College and seminary, and founder and president of Managing God’s Money. For information on business and personal financial strategy, visit https://www.managinggodsmoney.com/financial-tips-tools/

Data Science With Machine Learning

Today, technology has given birth to AI machines that have made our lives even easier. You may have experienced the wonders of AI while using social media sites, such as Google and Facebook. Many of these sites use the power of machine learning. In this article, we are going to talk about the relation between data science and machine learning. Read on.

What is Machine Learning?

Machine learning is the use of AI to help machines make predictions based on previous experience. We can say that ML is the subset of AI. The quality and authenticity of the data is representative of your model. The outcome of this step represents the data that will be used for the purpose of training.

After the assembling of data, it’s prepared to train the machines. Afterwards, filters are used to eliminate the errors and handle the missing data type conversions, normalization, and missing values.

For measuring the objective performance of a certain model, it’s a good idea to use a combo of different metrics. Then you can compare the model with the past data for testing purposes.

For performance improvement, you have to tune the model parameters. Afterwards, the tested data is used to predict the model performance in the real world. This is the reason many industries hire the services of machine learning professionals for developing ML based apps.

What is Data Science?

Unlike machine learning, data scientists use math, stats and subject expertise in order to collect a large amount of data from different sources. Once the data is collected, they can apply ML sentiment and predictive analysis to get fresh information from the collected data. Based on the business requirement, they understand data and provide it for the audience.

Data Science Process

For defining the data science process, we can say that there are different dimensions of data collection. They include data collection, modeling, analysis, problem solving, decision support, designing of data collection, analysis process, data exploration, imagining and communicating the results, and giving answers to questions.

We can’t go into the details of these aspects as it will make the article quite longer. Therefore, we have just mentioned each aspect briefly.

Machine Learning relies heavily on the available data. Therefore, they have a strong relationship with each other. So, we can say that both the terms are related.

ML is a good choice for data science. The reason is that data science is a vast term for different types of disciplines. Experts use different techniques for ML like supervised clustering and regression. On the other hand, data science is a comprehensive term that may not revolve around complex algorithms.

However, it is used to structure data, look for compelling patterns and advise decision-makers so that they can revolutionize business needs.

The Takeaway

So, if you are interested in data science or machine learning, we suggest that you take a data science course in Pune or go for a course about machine learning training in Pune. With these courses, you can get a much better idea of what ML or data science is all about.

Article Source: http://EzineArticles.com/10249988

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